A concentrator optimization design method based on energy flow density homogenization and concentrator

Abstract

This application discloses a concentrator optimization design method and a concentrator based on energy flux density homogenization, belonging to the field of concentrator design. The concentrator includes a reflective surface and a receiving surface. The concentrator optical optimization design method includes: obtaining the cross-sectional optical path diagram of the concentrator based on the mapping relationship between incident and reflected rays and constructing a concentrator structural model; mathematically solving the concentrator structural model to obtain the structural parameters of the concentrator; optimizing the concentrator design based on the structural parameters to obtain the target concentrator; performing optical simulation of the target concentrator using the Monte Carlo ray tracing method to obtain the energy flux density distribution of reflected rays on the receiving surface; and adjusting the structural parameters of the target concentrator based on the energy flux density distribution and the concentrator structural model to achieve a uniform energy flux density distribution on the receiving surface. The method provided in this application homogenizes the energy flux density of the focal spot, ensuring the performance and long-term stability of the concentrator.

Description

Technical Field

[0001] This application relates to a concentrator optimization design method and a concentrator based on energy flux density homogenization, belonging to the field of concentrator design. Background Technology

[0002] Due to atmospheric weakening, day-night cycles, weather phenomena such as clouds, fog, rain, and snow, and the influence of seasonal climate, the average energy density of sunlight reaching the Earth's surface is relatively low. According to open-source data from NASA's meteorological database, the average annual solar radiation outside the atmosphere is 1353 W / m². Under ideal conditions, at least 1 m² of photovoltaic panels are needed to achieve a power output of 1 kW. For space-based solar power stations, directly utilizing large-area photovoltaic panels for photoelectric conversion results in excessive mass. Therefore, a lightweight concentrator structure is proposed to concentrate sunlight into a small area for high-efficiency photoelectric conversion. Thus, the design purpose of the concentrator is to concentrate low-density energy onto a smaller receiving plane to increase energy transmission density and thereby improve photoelectric conversion efficiency.

[0003] Large-scale disc-shaped solar concentrators designed using existing methods mostly focus solar energy onto a collector medium (such as water or molten salt). The medium generates high-temperature steam to drive a Stirling motor or Brayton cycle generator, first converting light energy into heat energy, and then from heat energy into electrical energy. This not only results in a large overall device mass but also the accumulation of optical errors due to multiple reflections. Furthermore, disc-shaped parabolic concentrators are point-focusing concentrators. When parallel light shines on the concentrator's reflective surface, the solar energy is focused into a tiny spot that illuminates the receiving surface. This results in a high local energy flux density, causing a rapid increase in temperature on the receiving surface. This can lead to the photovoltaic panels detaching due to high temperatures, ultimately affecting the concentrator's performance and stability. Summary of the Invention

[0004] The purpose of this application is to provide a concentrator optimization design method and a concentrator based on energy flux density homogenization. The method homogenizes the energy flux density of the focal spot, ensuring the concentrator's performance and long-term stability. Furthermore, a concentrator is designed based on the concentrator optimization design method, achieving a uniform distribution of energy flux density on the receiving plane.

[0005] To achieve the above objectives, the first aspect of this application provides a concentrator optimization design method based on energy flux density homogenization. The concentrator is a single-reflection design, comprising a reflective surface for reflecting incident light and a receiving surface for receiving reflected light emitted from the reflective surface. The reflective surface is a centrally axis-symmetric paraboloid of revolution, and a circular notch is provided at the central axis position of the reflective surface. The receiving surface is disposed on the focal plane of the reflective surface. The concentrator optical optimization design method includes:

[0006] The cross-sectional optical path diagram of the concentrator is obtained based on the mapping relationship between the incident ray and the reflected ray;

[0007] Construct a concentrator structural model based on the cross-sectional optical path diagram;

[0008] The structural model of the condenser is mathematically solved to obtain the structural parameters of the condenser. The condenser is then optimized based on the structural parameters to obtain the target condenser. The structural parameters include the opening diameter of the reflective surface, the diameter of the circular cut, the diameter of the receiving surface, and the focal length of the condenser.

[0009] The target concentrator was optically simulated using the Monte Carlo ray tracing method to obtain the energy flux density distribution of reflected light on the receiving surface of the target concentrator.

[0010] Based on the energy flux density distribution and the concentrator structure model, the structural parameters of the target concentrator are adjusted to ensure a uniform energy flux density distribution on the receiving surface.

[0011] In one embodiment, obtaining the cross-sectional optical path diagram of the concentrator based on the mapping relationship between the incident and reflected rays includes:

[0012] A three-dimensional coordinate system is established with the central axis of the reflective surface of the concentrator as the origin o;

[0013] The cross-sectional optical path diagram of the concentrator is obtained based on the mapping relationship between the incident and reflected rays and the three-dimensional coordinate system, wherein the cross-sectional optical path diagram is the cross-sectional optical path diagram of the concentrator in the yoz plane.

[0014] In one embodiment, constructing the concentrator structural model based on the cross-sectional optical path diagram includes:

[0015] The coordinates of the incident point on the reflecting surface and the coordinates of the receiving point on the receiving surface are determined. Based on the coordinates of the incident point and the receiving point, the mapping relationship between the corresponding regions on the reflecting and receiving surfaces is determined. At the same time, the concentrator structure model is obtained by combining the principle of light reflection and the trigonometric function half-angle formula.

[0016] In one embodiment, the step of mathematically solving the concentrator structural model to obtain the concentrator's structural parameters includes:

[0017] The concentrator structural model is solved by combining differential methods and numerical calculation analysis methods.

[0018] In one embodiment, optimizing the design of the concentrator based on the structural parameters includes:

[0019] The concentrator is optimized based on its structural parameters to obtain the target concentrator, wherein the target concentrator has an opening diameter of 1000mm on its reflective surface, a circular cut diameter of 80mm, a receiving surface diameter of 80mm, and a focal length of 800mm.

[0020] In one embodiment, the optical simulation of the target concentrator using Monte Carlo ray tracing includes:

[0021] The distribution function of the incident light rays on the reflective surface of the target concentrator is determined based on the three-dimensional coordinate system.

[0022] Based on the distribution function, the parametric equations of the reflected ray are established according to the law of light reflection.

[0023] The receiving surface of the target concentrator is divided into several square regions, and the area of ​​each square region is determined.

[0024] Determine the number of incident rays and the incident solar radiation energy flux density, and calculate the energy carried by each reflected ray;

[0025] The number of reflected rays received in each square region is determined based on the number of incident rays and the parametric equations of reflected rays;

[0026] Based on the number of reflected rays received in each square region, the energy carried by each reflected ray, and the area of ​​each square region, the energy flux density distribution within each square region is obtained using the Monte Carlo ray tracing method.

[0027] In one embodiment, after obtaining the energy flux density distribution of the reflected light on the receiving surface of the target concentrator, the method further includes:

[0028] Calculate the geometric focusing ratio and optical focusing ratio of the target concentrator;

[0029] The adjustment of the structural parameters of the target concentrator based on the energy flux density distribution and the concentrator structural model includes:

[0030] The structural parameters of the target concentrator are adjusted based on the energy flux density distribution, the geometric concentration ratio, the optical concentration ratio, and the concentrator structural model.

[0031] In one embodiment, adjusting the structural parameters of the target concentrator based on the energy flux density distribution, the geometric concentration ratio, the optical concentration ratio, and the concentrator structural model includes:

[0032] Determine whether the energy flux density distribution, geometric concentration ratio, and optical concentration ratio of the target concentrator all meet the preset conditions. If so, there is no need to adjust the structural parameters of the target concentrator. Otherwise, fine-tune the structural parameters of the target concentrator according to the concentrator structure model until the energy flux density distribution, geometric concentration ratio, and optical concentration ratio of the target concentrator all meet the preset conditions.

[0033] A second aspect of this application provides a concentrator designed based on the concentrator optical optimization design method as described in the first aspect above or any embodiment of the first aspect above.

[0034] A third aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the first aspect or any embodiment of the first aspect.

[0035] As can be seen from the above, this application provides a concentrator optimization design method based on energy flux density homogenization. It designs the energy flux density of the focal spot to be homogenized and performs optical simulation of the improved target concentrator using the Monte Carlo ray tracing method, so that the energy flux density is uniformly distributed on the receiving plane of the final concentrator, thus ensuring the performance and long-term stability of the concentrator.

[0036] This application also provides a concentrator that directly converts light energy into electrical energy by focusing sunlight onto a focal plane, omitting the heat conversion step. Furthermore, to reduce the overall device mass and avoid the accumulation of optical errors caused by multiple reflections, the concentrator employs a single-reflection design, directly focusing sunlight onto the light-receiving plane of the focal plane, and then utilizing the photoelectric effect of a high-concentration photovoltaic panel to convert it into electrical energy. Simultaneously, by changing the shape of the reflecting plane, incident light rays illuminating different areas of the reflecting plane are mapped onto corresponding areas of the receiving plane, thereby achieving a uniform distribution of energy flux density on the receiving plane. This corresponding-area mapping method avoids problems such as light spot deviation and uneven energy distribution. Through this improved design, the concentrator provided in this application can better utilize light energy and meet various practical application needs. Attached Figure Description

[0037] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0038] Figure 1This is a schematic diagram of the structure of a concentrator provided in an embodiment of this application;

[0039] Figure 2 An optical path analysis diagram of a concentrator provided in an embodiment of this application;

[0040] Figure 3 A cross-sectional optical path diagram of a concentrator in the yoz plane is provided for embodiments of this application;

[0041] Figure 4 A schematic diagram illustrating the mapping relationship between incident and reflected light rays provided in an embodiment of this application;

[0042] Figure 5 A schematic diagram of a concentrator structure model calculation provided in this application embodiment;

[0043] Figure 6 A schematic flowchart of a Monte Carlo ray tracing method provided for an embodiment of this application;

[0044] Figure 7 A schematic diagram illustrating the focusing effect of an ideal parabolic concentrator provided in this application embodiment;

[0045] Figure 8 A schematic diagram illustrating the positional modification of the receiving surface of an ideal parabolic concentrator, provided in an embodiment of this application;

[0046] Figure 9 A power flux density distribution diagram of an ideal parabolic concentrator provided in an embodiment of this application;

[0047] Figure 10 A comparison diagram of the projection of an ideal parabolic surface and the reflective surface of a target concentrator onto the yoz plane, provided for embodiments of this application;

[0048] Figure 11 This application provides an embodiment of an energy flux density distribution diagram of an ideal parabolic receiving surface under parallel light illumination.

[0049] Figure 12 This application provides an embodiment of an energy flux density distribution map of the reflective surface of a target concentrator under parallel light illumination;

[0050] Figure 13 This application provides an embodiment of an energy flux density distribution diagram of an ideal parabolic receiving surface under solar radiation distribution.

[0051] Figure 14 This application provides an embodiment of an energy flux density distribution map of the reflective surface of a target concentrator under solar radiation conditions. Detailed Implementation

[0052] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods are omitted so as not to obscure the description of this application with unnecessary detail.

[0053] It should be understood that, when used in this specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0054] It should also be understood that the terminology used in this application specification is for the purpose of describing particular embodiments only and is not intended to limit the application. As used in this application specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0055] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0056] Many specific details are set forth in the following description 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. Those skilled in the art can make similar extensions without departing from the spirit of this application. Therefore, this application is not limited to the specific embodiments disclosed below.

[0057] Example 1

[0058] This application provides a concentrator optimization design method based on energy flux density homogenization, such as... Figure 1 As shown, the concentrator is a single-reflection design. The concentrator includes a reflective surface 10 for reflecting incident light and a receiving surface 20 for receiving reflected light emitted from the reflective surface 10. The reflective surface 10 is a paraboloid of revolution symmetrical about a central axis. A circular cutout 11 is provided at the central axis position of the reflective surface 10. The receiving surface 20 is disposed on the focal plane of the reflective surface 10.

[0059] The optical optimization design method for the concentrator includes:

[0060] S100 obtains the cross-sectional optical path diagram of the concentrator based on the mapping relationship between the incident and reflected rays;

[0061] Optionally, obtaining the cross-sectional optical path diagram of the concentrator based on the mapping relationship between the incident and reflected rays includes:

[0062] A three-dimensional coordinate system is established with the central axis of the reflective surface 10 of the concentrator as the origin o;

[0063] The cross-sectional optical path diagram of the concentrator is obtained based on the mapping relationship between the incident and reflected rays and the three-dimensional coordinate system, wherein the cross-sectional optical path diagram is the cross-sectional optical path diagram of the concentrator in the yoz plane.

[0064] In one implementation, the three-dimensional coordinate system established in this application embodiment is as follows: Figure 2 As shown, the cross-sectional optical path diagram of the concentrator in the yoz plane is as follows. Figure 3 As shown, Figure 3 In this diagram, D represents the opening diameter of the concentrator's reflective surface 10, d represents the diameter removed from the bottom of the concentrator, w represents the diameter of the receiving surface 20, and f represents the focal length of the concentrator. The starting coordinate point of the generatrix of the yoz plane of the concentrator's reflective surface 10 is A(d / 2,0), and the ending coordinate point is B(D / 2,y). Parallel light incident on the concentrator's reflective surface 10 is reflected to the corresponding G(0,f) and H(w / 2,f) on the receiving plane. At this point, each beam of light incident on the concentrator's reflective surface 10 can be mapped onto the receiving surface 20 of the concentrator.

[0065] S200 constructs a concentrator structural model based on the cross-sectional optical path diagram;

[0066] Optionally, constructing the concentrator structure model based on the cross-sectional light path diagram includes: determining the coordinates of the incident point of the incident light on the reflecting surface 10 and the coordinates of the receiving point on the receiving surface 20 after the incident light is reflected; determining the mapping relationship of the corresponding regions of the incident light on the reflecting surface 10 and the receiving surface 20 based on the incident point coordinates and the receiving point coordinates; and obtaining the concentrator structure model by combining the principle of light reflection and the trigonometric function half-angle formula.

[0067] In one embodiment, based on parabolic geometry, when light emitted from the focus of a parabola strikes the parabolic surface, the reflected light exits in a direction parallel to the opening of the parabola. Since the light path is reversible, this embodiment utilizes a parabolic surface to focus approximately parallel sunlight onto the focal plane. Simultaneously, to ensure the performance and long-term stability of the concentrator, the geometry of the concentrator's reflective surface 10 is designed to homogenize the energy flux density focused onto the concentrator's receiving surface 20. Among these design considerations, the mapping between the focusing area of ​​the reflective surface 10 and the light-receiving area of ​​the receiving surface 20 is a critical design factor, affecting the performance of the entire optical system. For example... Figure 4 As shown, the newly designed concentrator in this embodiment of the application, by changing the shape of the reflective surface 10, enables the light rays illuminating the incident area I of the reflective surface 10 to be mapped onto the corresponding area of ​​the reflective area II of the receiving surface 20, thereby achieving a uniform distribution of energy flux density on the receiving surface 20. This mapping method of corresponding areas can avoid the problems of light spot deviation and uneven energy distribution. Through this improved design, the embodiments of this application can better utilize light energy and meet various practical application needs.

[0068] In one implementation, the shape of the concentrator's reflective surface 20 can be calculated by establishing a mathematical model. To achieve this, embodiments of this application utilize a yoz cross-sectional ray diagram to calculate the generatrix of the paraboloid of revolution of the concentrator's reflective surface 10, thereby obtaining a more accurate mathematical model. The curvature of the concentrator's reflective surface 10 can then be represented by the established mathematical model. This process determines the radius and curvature of the concentrator's reflective surface 10, as well as parameters such as the diameter of the bottom notch of the reflective surface 10. During the calculation, the incident light ray can be parallel to the z-axis to simplify the calculation, such as... Figure 5 As shown, let J(Y,Z) be the incident point of a beam of light incident on any point on the reflective surface 10 of the concentrator, and let K(u,f) be the point on the receiving surface 20 after the beam is reflected. The geometric relationship is as follows:

[0069] Z′=tanβ

[0070]

[0071] The corresponding region mapping relationship is as follows:

[0072]

[0073] According to the principle of light reflection in a plane:

[0074] θ=2β

[0075] Calculated using the trigonometric function half-angle formula:

[0076]

[0077]

[0078] Combining the two formulas and eliminating u, we get:

[0079]

[0080]

[0081] By combining the two formulas above, we can obtain the following concentrator structural model:

[0082]

[0083] In the formula, D is the diameter of the opening of the reflective surface 10 (mm); d is the diameter of the circular cutout 11 removed from the bottom of the reflective surface 10 (mm); w is the diameter of the receiving surface 20 (mm); and f is the focal length of the condenser (mm).

[0084] In one embodiment, based on the concentrator structural model, in order to maximize the reception of light by the concentrator reflective surface 10, the circular cutout 11 at the bottom of the concentrator should be as small as possible. Furthermore, the diameter of the circular cutout 11 at the bottom of the concentrator should be equal to the diameter of the receiving surface 20, thus ensuring that light can be completely reflected onto the receiving surface 20.

[0085] S300 performs mathematical solutions on the concentrator structure model to obtain the concentrator's structural parameters, and optimizes the concentrator design based on the structural parameters to obtain the target concentrator. The structural parameters include the opening diameter of the reflective surface 10, the diameter of the circular cutout 11, the diameter of the receiving surface 20, and the focal length of the concentrator.

[0086] Optionally, the concentrator structural model can be solved by combining differential methods and numerical calculation analysis methods, and the concentrator can be optimized based on the structural parameters of the concentrator obtained from the solution to obtain the target concentrator.

[0087] In one embodiment, the target concentrator reflective surface 10 has an opening diameter of 1000 mm, the circular cutout 11 has a diameter of 80 mm, the receiving surface 20 has a diameter of 80 mm, and the concentrator's focal length is 800 mm. Alternatively, other structural parameters may be used, which are not limited here.

[0088] S400 uses the Monte Carlo ray tracing method (MCRT) to perform optical simulation on the target concentrator and obtain the energy flux density distribution of the reflected light on the receiving surface 20 of the target concentrator;

[0089] The main idea of ​​Monte Carlo methods is to establish a probabilistic model, using the parameters describing the problem as the objective, and then conduct random trials through this model, performing large-scale sampling and using statistical methods to estimate the parameters and approximate the solution for the desired parameters. Ray tracing, on the other hand, utilizes the reversibility of light, tracing the received light backwards from the receiving point back to the source to obtain information about the source. The MCRT method combines Monte Carlo and ray tracing, describing light emission as a stochastic model problem, determining the propagation path and collision point location of each ray after it interacts with surfaces (reflection or absorption) following collisions.

[0090] In one implementation, achieving uniform energy flux density distribution is a critical issue in the design of a concentrator. It requires careful consideration of optical principles and the geometric characteristics of the concentrator to ensure its performance and long-term stability. The embodiments of this application use the MCRT method to perform optical simulation of the concentrator, with the following steps: (1) Representing solar irradiance with rays, where each ray has equal energy; (2) Determining the ray emission position using a selected solar model, and determining the energy after collision with the surface using reflectivity and absorptivity; (3) Determining the transmission path of the reflected rays using the law of reflection; (4) Statistically calculating the intersection points of rays on the receiving surface to obtain the energy flux density distribution on the receiving surface. The calculation process is as follows: Figure 6 As shown, the steps for calculating the energy retention density distribution are as follows:

[0091] The S410 paraboloid of revolution is centrally symmetric, therefore, only the generatrix 10 of the concentrator's reflecting surface needs to be analyzed. According to... Figure 2 The three-dimensional coordinate system shown determines the distribution function of the incident ray on the reflective surface 10 of the target concentrator, where f is the distance from the receiving surface 20 to the reflective surface 10. A ray is randomly generated with an incident point P, and the coordinates of point P in the global coordinate system are (x...). p ,y p ,z p The distance from the ray to the z-axis is y. p The distribution function is:

[0092]

[0093] By sampling the light, we can obtain:

[0094]

[0095] In the formula, D is the diameter of the opening 10 on the reflective surface of the concentrator (mm); x1 is a random number from 0 to 1.

[0096] S420 calculates the unit vector of the reflected ray direction based on the distribution function and the proposed ray reflection theorem, assuming the reflected ray point (x... q ,y q,z q Establish the parametric equations for the reflected rays:

[0097]

[0098] Where t is a parameter, (n x ,n y ,n z ) is the unit vector in the PQ direction.

[0099] S430 divides the largest envelope square region, S, located on the focal plane receiving surface 20, into N parts. c ×N c The area of ​​each of the small square regions is:

[0100]

[0101] The incident solar radiation flux density at S440 is E in The energy flux density incident on the concentrator is considered as N rays with uniform energy flux density. Simulations have verified that N is typically taken as 2 × 10⁻⁶. 6 The desired accuracy can be achieved with a short calculation time. After actual reflective coating, the reflectivity of the concentrator's reflective surface 10 is 0.95, and the energy of each light band is:

[0102]

[0103] S450 determines the number of reflected rays received in each square region based on the number of incident rays and the parametric equation of the reflected rays; specifically, the parametric equation of the reflected rays is combined with the z = f equation of the receiving surface to determine the coordinates (x, y) of the focal point P of the incident point on the reflective surface of the concentrator. p ,y p ,z p The focal distance d between the focal plane and the z-axis z for:

[0104]

[0105] By using the above method, the location of the light rays within the square can be determined. By repeatedly calculating, the number of light rays within each square region can be obtained.

[0106] S460 uses the Monte Carlo ray tracing method to obtain the energy flux density distribution within each square region, based on the number of reflected rays received within each square region, the energy carried by each reflected ray, and the area of ​​each square region. Specifically, in the calculation, solar energy is considered as a large number of uniform, parallel, and independent rays carrying energy. The number of rays within each square region is counted, and the energy flux density within each region is:

[0107]

[0108] In the formula, E k —Energy flux density of the k-th region (W / m²) 2 );S k —Area of ​​the kth region (m²) 2 );I n —The energy (W) delivered per second by the nth reflected ray.

[0109] Optionally, after obtaining the energy flux density distribution of the reflected light on the receiving surface 20 of the target concentrator, the method further includes: calculating the geometric concentration ratio and optical concentration ratio of the target concentrator.

[0110] In one implementation, the focusing effect of a concentrator can be evaluated using both geometric focusing ratio and optical focusing ratio to comprehensively consider its performance. Geometric focusing ratio refers to whether the physical shape of the concentrator effectively focuses light, while optical focusing ratio refers to whether the concentrator has an excellent optical path design to achieve efficient focusing. Furthermore, the uniformity of energy flux density can be obtained based on the energy flux density distribution, serving as a key indicator for evaluating the concentrator's focusing effect.

[0111] S500 adjusts the structural parameters of the target concentrator based on the energy flux density distribution and the concentrator structure model, so that the energy flux density on the receiving surface 20 is uniformly distributed.

[0112] In one embodiment, when calculating the geometric concentration ratio and optical concentration ratio of the target concentrator, the structural parameters of the target concentrator are adjusted according to the energy flux density distribution, the geometric concentration ratio, the optical concentration ratio, and the concentrator structural model.

[0113] Optionally, it can be determined whether the energy flux density distribution, geometric concentration ratio, and optical concentration ratio of the target concentrator all meet preset conditions. If so, there is no need to adjust the structural parameters of the target concentrator; otherwise, the structural parameters of the target concentrator are fine-tuned according to the concentrator structural model until the energy flux density distribution, geometric concentration ratio, and optical concentration ratio of the target concentrator all meet the preset conditions.

[0114] As can be seen from the above, the embodiments of this application provide a concentrator optimization design method based on energy flux density homogenization. The method homogenizes the energy flux density of the focal spot and performs optical simulation on the improved target concentrator using the Monte Carlo ray tracing method, so that the energy flux density is uniformly distributed on the receiving plane of the final concentrator, thus ensuring the performance and long-term stability of the concentrator.

[0115] Example 2

[0116] This application provides a concentrator designed based on the concentrator optical optimization design method described in any embodiment of this application.

[0117] As can be seen from the above, the concentrator provided in this application directly converts light energy into electrical energy by focusing sunlight onto the focal plane, omitting the heat energy conversion step. Furthermore, to reduce the overall device mass and avoid the accumulation of optical errors caused by multiple reflections, the concentrator employs a single-reflection design, directly focusing sunlight onto the light-receiving plane of the focal plane, and then utilizing the photoelectric effect of the high-concentration photovoltaic panel to convert it into electrical energy. Simultaneously, by changing the shape of the reflecting plane, the incident light rays illuminating each area of ​​the reflecting plane are mapped onto the corresponding areas of the receiving plane, thereby achieving a uniform distribution of energy flux density on the receiving plane. This mapping method of corresponding areas avoids problems such as light spot deviation and uneven energy distribution. Through this improved design, the concentrator provided in this application can better utilize light energy and meet various practical application needs.

[0118] Example 3

[0119] This application's embodiments verified the focusing effect of other concentrators designed to solve the problem of energy flux density uniformity. The specific experimental process is as follows:

[0120] For an ideal parabola, its light-gathering effect is as follows: Figure 7 As shown, an ideal parabolic concentrator is a point-focusing type, which focuses solar energy into a very small spot that illuminates the receiving surface. This results in a relatively high local energy flux density, causing the temperature of the receiving surface to rise rapidly, potentially leading to the photovoltaic panel detaching due to overheating. For a primary-reflection concentrator with an ideal parabolic surface, to ensure uniform energy flux density, the receiving surface can be moved closer to or further away from the reflecting surface along the optical axis of the concentrator. The position of the receiving surface can be adjusted as follows: Figure 8 As shown. To verify its focusing effect, the receiving surface was first designed as a circular receiving device with a diameter of d. Simulation calculations using the MCRT method revealed that when sunlight shines on the reflecting surface, its energy flux density distribution is as follows. Figure 9As shown, because the circular receiving surface blocks sunlight projected onto the concentrator's reflective surface, the energy flux density on the receiving surface becomes uneven, resulting in a significant gradient decrease in energy flux density in the central region compared to other regions. Regardless of whether the receiving surface is moved closer to or further away from the concentrator's reflective surface along the optical axis, the central region cannot receive reflected light. This is because when the circular receiving surface moves up and down, it will inevitably block the incident light illuminating the projection area. In summary, after optical simulation, the concentrator with altered receiving surface position exhibits a region at the center of its receiving surface where light cannot be received, resulting in an uneven distribution of energy flux density on the receiving surface.

[0121] This application also demonstrates the effect of the improved target concentrator through comparative experiments. The specific experimental process is as follows:

[0122] Based on the prototype setup requirements of D = 1m, w = 80mm, and f = 800mm, the yoz section is solved. Since obtaining the analytical expression for this equation is difficult, a numerical solution method is used. The parameters after the solution are shown in Table 1.

[0123] Table 1 Preliminary Design Parameters of Optical Model

[0124] name parameter Concentrator diameter D 1000mm Focal length f 800mm Remove diameter d 80mm Receiver diameter w 80mm Disc Depth H 71.69mm

[0125] To gain a more accurate understanding of the condenser's performance and to consider all key aspects in the final evaluation to determine whether the condenser meets the required focusing effect, the embodiments of this application set the following focusing performance evaluation indicators:

[0126] Geometric concentration ratio refers to the area A of the concentrator that receives incident light. in With the receiving area A of the reflected light out The geometric concentration ratio is the ratio of light gathering to light focusing. A higher geometric concentration ratio indicates a stronger light-gathering ability and better focusing effect of the concentrator, and it can reflect the light-gathering performance of the concentrator to a certain extent. Generally, the geometric concentration ratio is used instead of the optical concentration ratio to roughly measure the light-gathering performance of the concentrator and to calibrate the parameters of the initial design of the concentrator.

[0127] Geometric Concentration Ratio C R Represented as:

[0128]

[0129] Optical focusing ratio typically refers to the average optical energy flux density E on the receiving surface. out The average energy flux density E incident on the reflective surface of the concentrator inThe optical focusing ratio (ORR) is the ratio of light focused by the condenser to light focused by the geometric focusing ratio. A higher optical focusing ratio indicates a stronger ability to focus light and a better focusing effect. Compared to the geometric focusing ratio, the optical focusing ratio more comprehensively reflects the focusing performance of the condenser and is an important reference parameter for evaluating the focusing effect of the condenser.

[0130] The optical focusing ratio C is expressed as:

[0131]

[0132] For concentrating systems, the uniformity of energy flux density on the receiving surface of the concentrator is one of the standards for evaluating the optical performance of the concentrator. Energy flux density uniformity refers to whether the shape of the focused light spot is uniform. If the light spot is not uniform, some areas may be brighter or darker than others, which will affect the accuracy and reliability in applications. Therefore, higher energy flux density uniformity means a more uniform light spot and better concentrator performance. Currently, there is no unified standard in the art for evaluating the energy flux density uniformity of solar concentrators. This application proposes a calculation formula for energy flux density uniformity based on the IEC60904-9 international standard for addressing energy flux density non-uniformity in solar simulators, referring to the homogenization of concentrated energy flux density in solar concentrators.

[0133]

[0134] In the formula, ΔE—uniformity of energy flux density; E max —Maximum energy flux density (W / m 2 ); E min Minimum energy flux density (W / m³) 2 ).

[0135] To verify the uniformity of the light spot on the reflective surface of the newly designed concentrator, this embodiment of the application uses MCRT for simulation analysis. During the analysis, the newly designed concentrator is compared with an ideal parabolic dish concentrator. Furthermore, to analyze the light distribution more comprehensively and meticulously, the receiver surface is divided into 128×128 grid regions for analysis.

[0136] To make the simulation results closer to reality, this embodiment sets the light source as a circular grid light source and ensures that the light is uniformly distributed within the illumination range. Furthermore, the light source intensity is set to 1361 W / m², based on the solar irradiance intensity outside the atmosphere in Harbin. 2 The wavelength of the light is 546.10 nm. Meanwhile, to ensure the accuracy of the light simulation, this embodiment uses 2×102 6 The light rays were simulated.

[0137] The concentrator's reflective surface is made of an aluminum-coated mirror with a reflectivity of 95%. During the simulation, this embodiment used a solar angle of 0.287° and parallel light parallel to the z-axis as the incident light. In this way, the distribution of light can be observed and analyzed more comprehensively, so as to better evaluate the performance of the concentrator.

[0138] In summary, rigorous parameter settings were employed during the simulation process, and the Monte Carlo ray tracing method was used for thorough analysis and comparison, providing a scientific basis and effective means for evaluating the performance of the concentrator.

[0139] The concentrator parameters are compared in Table 2:

[0140] Table 2 Concentrator System Structural Parameters

[0141]

[0142] The results were calculated based on the given design specifications for the concentrator's reflective surface, and the corresponding data were obtained. These results were then compared with those of an ideal parabolic dish concentrator, as shown below. Figure 10 As shown, the projection of the improved target concentrator onto the reflector surface of the yoz plane concentrator is significantly smaller than that of the ideal parabolic concentrator.

[0143] (1) Simulation results of an ideal parabolic surface under parallel light illumination

[0144] like Figure 11 As shown, when parallel light is incident on an ideal parabolic concentrator, the light is reflected and focused onto the receiving surface. However, there is a significant problem with the energy flux density distribution; the concentrated area is only located in the central region of the receiver, and the diameter of the focused light spot is only 7.73 mm. Meanwhile, light is not effectively concentrated in other areas, making it difficult to meet the requirement of uniform energy acquisition across the entire receiving surface. Observing the energy flux density distribution images of the xoz and yoz sections on the receiving surface reveals a Gaussian distribution. The energy flux density rapidly decreases to 0 with increasing distance from the center of the receiving surface. However, the energy distribution across the entire receiving surface is highly uneven, causing the concentrated solar energy to focus only on an area with a diameter of 7.73 mm centered on the receiver surface. This leads to significant temperature inhomogeneity on the receiving surface, making the temperature in this area easily rise, resulting in problems such as photovoltaic panel detachment. This not only shortens the concentrator's lifespan but also damages the overall structure of the concentrator. Based on optical evaluation indicators, [the following is a concentrator analysis]... Figure 11 The key data shown refers to the calculation of parameters in optical evaluation indicators, specifically the geometric concentration ratio C. R =16628.00, optical focusing ratio C=156.24, energy flux density uniformity ΔE=0.

[0145] (2) Simulation results of improved concentrator reflector surface under parallel light illumination

[0146] like Figure 12 As shown, experiments were conducted using an improved target concentrator under parallel light incidence conditions, and the energy flux density distribution was analyzed. The experimental results show that the energy flux density distribution is relatively uniform after reflection from the concentrator's reflective surface to its receiving surface. Specifically, the energy flux density distribution is relatively uniform in a circular region with a diameter of 76.00 mm centered on the receiver center of the concentrator, and the energy flux density distribution on the receiving surface is within the range of 2.10 × 10⁻⁶. 5 W / m 2 Slight fluctuations were observed in the vicinity. However, within a circular region 10 mm in diameter centered on the receiver, the energy flux density fluctuated significantly, with the difference between the maximum and minimum values ​​reaching 2.00 × 10⁻⁶. 4 W / m 2 W / m 2 This is due to the leakage of light rays near the edge of the receiving plane after reflection from the concentrator's reflective surface to the concentrator's receiving surface. Furthermore, a large gradient in energy flux density was observed in the annular strip region with diameters between 76.00 mm and 80.00 mm, centered on the receiver center. This is likely due to light leakage at the edges during reflection. Based on simulation results, after extraction... Figure 12 The key data shown is used to calculate the geometric concentration ratio C for parameters in the optical evaluation index. R =163.31, optical focusing ratio C =153.75, energy flux density uniformity ΔE =86.79%.

[0147] (3) Simulation results of an ideal parabolic concentrator under solar radiation distribution

[0148] like Figure 13 As shown, when sunlight is incident on an ideal parabolic concentrator according to the solar radiation distribution, the light rays exhibit a certain focusing shape under the influence of the concentrator's reflective surface. Through the design and optimization of the reflective surface, the light rays can be concentrated to the central region of the receiving surface. However, compared to the case of parallel light incidence, the diameter of the focused spot increases, reaching 13.70 mm, which can be clearly observed. On the receiving surface, the energy flux density distribution exhibits a Gaussian distribution, with a peak energy flux density of 2.18 × 10⁻⁶ at the center of the receiving surface. 7 W / m 2 .

[0149] However, as the light diffuses outwards from the center, the energy flux density rapidly decreases to zero. This means that in areas far from the focused spot, the concentration of solar energy is significantly reduced, and the energy transfer efficiency also drops dramatically. Therefore, the distribution of light received on the entire receiving surface is severely uneven. The area at the center of the receiving surface where the light is focused experiences extremely high temperatures due to the concentrated light projection. Compared to the surrounding areas, the instantaneous temperature difference in this region is very large. This large temperature difference can affect the receiving surface; prolonged exposure to high temperatures may cause the photovoltaic module to detach, or even damage the entire concentrator structure. (After extraction...) Figure 13 The key data shown is used to calculate the geometric concentration ratio C from the parameters in the optical evaluation index. R =5164.90, optical focusing ratio C =154.56, energy flux density uniformity ΔE =0.

[0150] (4) Simulation results of improved parabolic concentrator under solar radiation distribution

[0151] like Figure 14 As shown, under these solar radiation conditions, the light reflected by the concentrator is more likely to escape at the edge of the receiver plane compared to parallel light incidence, resulting in a relatively smaller area of ​​uniform energy flux density distribution. Specifically, within a circular region centered on the receiver center with a diameter of 71.64 mm, the energy flux density distribution is still relatively uniform, but the uniform distribution area is smaller than under parallel light incidence conditions. This is because sunlight forms a 0.287° light cone angle, making it easier for light to be reflected from the concentrator's reflective surface and onto the receiver. However, due to the edge effect of the concentrator's reflective surface, light easily escapes as it approaches the edge of the receiver plane. Therefore, the uniform distribution area centered on the receiver center is relatively small, and within this circular region, the energy flux density distribution is around 210,000 W / m². 2 Nearby, in addition to the area around the center of the receiver, the optical energy flux density distribution also exhibits a ring-shaped region with a diameter between 71.64 mm and 80 mm. Within this range, the edge effect becomes particularly pronounced, resulting in a significant amount of light not being reflected from the concentrator to the receiver, thus causing a noticeable decrease in energy flux density. Therefore, the optical design should fully consider the edge effect of the receiver plane and specifically optimize the shape of the concentrator to achieve a maximized energy flux density distribution. Based on the simulation results, after extraction... Figure 14 The key data shown refers to the calculation of parameters in optical evaluation indicators, specifically the geometric concentration ratio C. R =193.60, optical focusing ratio C =145.07, energy flux density uniformity ΔE =92.24%.

[0152] Table 3 summarizes the parameters of the ideal parabolic concentrator and the improved target concentrator under both parallel light illumination and solar radiation distribution conditions.

[0153] Table 3 Evaluation Indicators for Concentrating Performance Parameters

[0154]

[0155] The evaluation index table of focusing performance parameters and the optical simulation results show that, regardless of whether under parallel illumination or sunlight conditions, the uniformity of energy flux density on the receiving surface of the ideal parabolic concentrator is poor. The energy flux density of the focused spot is at its peak at the center of the receiving surface, and decreases rapidly along the center of the spot. For the ideal parabolic concentrator, the spot diameter is smaller under parallel illumination than under sunlight conditions. Therefore, the geometric focusing ratio is greater under parallel illumination than under sunlight conditions. Under both illumination conditions, since the spot diameter is smaller than the receiving surface diameter, the optical focusing ratio is not significantly different.

[0156] For the improved target concentrator, the diameter of the uniform area of ​​the light spot on the receiving surface under sunlight is smaller than that under parallel lighting. Therefore, the geometric concentration ratio under sunlight is greater than that under parallel lighting. However, due to the existence of the solar angle under sunlight, light reflected from the concentrator's reflective surface will escape from the edge area of ​​the receiver. Therefore, the optical concentration ratio under sunlight is less than that under parallel lighting, while the energy flux density uniformity is the opposite.

[0157] As can be seen from the above, the target concentrator provided in this application embodiment has a larger uniform energy flux density area compared to an ideal parabolic concentrator, which meets the requirement of uniform energy flux density received by the receiver, and the spot energy flux density in the uniform area is 2.1 × 10⁻⁶. 5 W / m 2 nearby.

[0158] It should be understood that if the integrated modules / units described above are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable storage medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction.

[0159] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0160] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the above device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0161] It should be noted that the methods and detailed examples provided in the above embodiments can be incorporated into the apparatus and devices provided in the embodiments, and can be referred to each other, without further elaboration.

[0162] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0163] In the embodiments provided in this application, it should be understood that the disclosed apparatus / terminal devices and methods can be implemented in other ways. For example, the apparatus / device embodiments described above are merely illustrative. For instance, the division of the modules or units described above is merely a logical functional division, and in actual implementation, it can be divided in other ways. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed.

[0164] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A concentrator optimization design method based on energy flux density homogenization, characterized in that, The concentrator is a single-reflection design. The concentrator includes a reflective surface (10) for reflecting incident light and a receiving surface (20) for receiving reflected light emitted from the reflective surface (10). The reflective surface (10) is a paraboloid of revolution symmetrical about a central axis. A circular cutout (11) is provided at the central axis position of the reflective surface (10). The receiving surface (20) is located on the focal plane of the reflective surface (10). The optical optimization design method for the concentrator includes: The cross-sectional optical path diagram of the concentrator is obtained based on the mapping relationship between the incident ray and the reflected ray; Construct a concentrator structural model based on the cross-sectional optical path diagram; The structural model of the concentrator is mathematically solved to obtain the structural parameters of the concentrator. The concentrator is then optimized based on the structural parameters to obtain the target concentrator. The structural parameters include the opening diameter of the reflective surface (10), the diameter of the circular cut (11), the diameter of the receiving surface (20), and the focal length of the concentrator. The target concentrator was optically simulated using the Monte Carlo ray tracing method to obtain the energy flux density distribution of the reflected light on the receiving surface (20) of the target concentrator. The structural parameters of the target concentrator are adjusted according to the energy flux density distribution and the concentrator structure model so that the energy flux density on the receiving surface (20) is uniformly distributed. The process of obtaining the cross-sectional optical path diagram of the concentrator based on the mapping relationship between the incident and reflected rays includes: A three-dimensional coordinate system is established with the central axis of the reflective surface (10) of the concentrator as the origin o; The cross-sectional optical path diagram of the concentrator is obtained based on the mapping relationship between the incident ray and the reflected ray and the three-dimensional coordinate system, wherein the cross-sectional optical path diagram is the cross-sectional optical path diagram of the concentrator in the yoz plane; The process of constructing the concentrator structural model based on the cross-sectional optical path diagram includes: The coordinates of the incident point on the reflecting surface (10) and the coordinates of the receiving point on the receiving surface (20) after the incident light is reflected are determined. Based on the coordinates of the incident point and the receiving point, the mapping relationship of the corresponding regions on the reflecting surface (10) and the receiving surface (20) is determined. At the same time, the concentrator structure model is obtained by combining the principle of light reflection and the trigonometric function half-angle formula.

2. The concentrator optimization design method as described in claim 1, characterized in that, The step of mathematically solving the concentrator structural model to obtain the concentrator's structural parameters includes: The concentrator structural model is solved by combining differential methods and numerical calculation analysis methods.

3. The concentrator optimization design method as described in claim 1, characterized in that, The optimization design of the concentrator based on the structural parameters includes: The concentrator is optimized according to its structural parameters to obtain the target concentrator, wherein the opening diameter of the reflective surface (10) of the target concentrator is 1000mm, the diameter of the circular cut (11) is 80mm, the diameter of the receiving surface (20) is 80mm, and the focal length of the concentrator is 800mm.

4. The concentrator optimization design method as described in claim 1, characterized in that, The optical simulation of the target concentrator using the Monte Carlo ray tracing method includes: The distribution function of the incident light on the reflective surface (10) of the target concentrator is determined according to the three-dimensional coordinate system; Based on the distribution function, the parametric equations of the reflected ray are established according to the law of light reflection. The target concentrator receiving surface (20) is divided into several square regions, and the area of ​​each square region is determined; Determine the number of incident rays and the incident solar radiation energy flux density, and calculate the energy carried by each reflected ray; The number of reflected rays received in each square region is determined based on the number of incident rays and the parametric equations of reflected rays; Based on the number of reflected rays received in each square region, the energy carried by each reflected ray, and the area of ​​each square region, the energy flux density distribution within each square region is obtained using the Monte Carlo ray tracing method.

5. The concentrator optimization design method as described in claim 1, characterized in that, The process of obtaining the energy flux density distribution of the reflected light on the receiving surface (20) of the target concentrator further includes: Calculate the geometric focusing ratio and optical focusing ratio of the target concentrator; The adjustment of the structural parameters of the target concentrator based on the energy flux density distribution and the concentrator structural model includes: The structural parameters of the target concentrator are adjusted based on the energy flux density distribution, the geometric concentration ratio, the optical concentration ratio, and the concentrator structural model.

6. The concentrator optimization design method as described in claim 5, characterized in that, The adjustment of the structural parameters of the target concentrator based on the energy flux density distribution, the geometric concentration ratio, the optical concentration ratio, and the concentrator structural model includes: Determine whether the energy flux density distribution, geometric concentration ratio, and optical concentration ratio of the target concentrator all meet the preset conditions. If so, there is no need to adjust the structural parameters of the target concentrator. Otherwise, fine-tune the structural parameters of the target concentrator according to the concentrator structural model until the energy flux density distribution, geometric concentration ratio, and optical concentration ratio of the target concentrator all meet the preset conditions.

7. A concentrator, characterized in that, The concentrator is designed based on the concentrator optical optimization design method as described in any one of claims 1 to 6.

8. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 6.

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