Heliostat field optimization method based on ray tracing model and NSGA-II algorithm

Abstract

The invention provides a heliostat field optimization method based on a ray tracing model and an NSGA-II algorithm. The heliostat field optimization method comprises the following steps: S1, acquiring environmental information of a heliostat field and facility limitation parameters of the heliostat field; s2, the environment information and the limiting parameters are preprocessed; s3, determining the shadow area and the reflective area of each heliostat; determining the cut-off efficiency of the heat collector; s4, constructing an NSGA-II optimization model, inputting the preprocessed environment information, the preprocessed limiting parameters, the shadow area and the light-emitting area of the heliostat and the cut-off efficiency of the heat collector into the NSGA-II optimization model to obtain a heliostat field layout result, and displaying the heliostat field layout result through a visual interface; the method comprises the following steps: acquiring environmental parameters and limiting parameters of an actual target position of a heliostat field, determining a shadow area and a reflective area of each heliostat of the heliostat field, and inputting the parameters to SAamp; and in the NSGA-II algorithm model, optimal heliostat field structure parameters are obtained, so that the solar energy utilization rate can be effectively improved, and the solar power generation efficiency is improved.

Description

Technical Field

[0001] The present invention relates to an optimization method, and in particular to a heliostat field optimization method based on a ray tracing model and a SA&NSGA-II algorithm. Background Art

[0002] With the development of human society, the field of new energy has received more and more attention. At present, the fossil fuels that the world mainly relies on have limited reserves and serious environmental pollution, which is contrary to the low-carbon and carbon-free concepts promoted globally. Therefore, the development of clean energy is of great significance to solving the current energy crisis and environmental problems. This energy transformation is based on an objective analysis of the actual situation and is also a necessary choice for achieving sustainable development. Solar energy is a clean and pollution-free energy source. As an emerging solar power generation system, the daytime mirror system has received more and more attention. Through the efficient use of solar energy through the daytime mirror field, it is helpful to achieve sustainable energy goals, reduce negative impacts on the environment, and promote the coordinated development of economy, society and environment. The tower solar thermal power generation system uses point focusing technology to use the heliostat field to concentrate the direct radiation energy of the sun to the absorber, thereby heating the energy storage medium. Subsequently, these heated media are converted into steam through the heat exchange system to drive the steam turbine to generate electricity.

[0003] The tower solar thermal power station collects solar energy through a large number of heliostats, so that the low-density solar energy is reflected to the collector at the top of the tower and concentrated into high-density solar energy. The collector then converts the light energy into working fluid heat energy, and the steam turbine generator converts the heat energy into electrical energy. The design of the heliostat field is crucial to improving the efficiency and performance of the solar thermal power station.

[0004] In solar thermal power plants, especially tower plants, a large number of heliostats are used to collect sunlight and reflect it to the collector. The layout of the heliostats has a significant impact on the efficiency and performance of the power plant. Traditional layout methods may not fully utilize solar energy or may cause shadowing problems.

[0005] Therefore, in order to solve the above-mentioned technical problems, it is urgent to propose a new technical means. Summary of the invention

[0006] In view of this, the purpose of the present invention is to provide a heliostat field optimization method based on a ray tracing model and a SA&NSGA-II algorithm, by obtaining the environmental parameters and restriction parameters of the actual target position of the heliostat field, and determining the shadow area and reflection area of ​​each heliostat in the heliostat field, and inputting these parameters into the SA&NSGA-II algorithm model to obtain the optimal heliostat field structure parameters, thereby effectively improving the utilization rate of solar energy and the efficiency of solar power generation.

[0007] The present invention provides a heliostat field optimization method based on a ray tracing model and an NSGA-II algorithm, comprising the following steps:

[0008] S1. Obtaining environmental information of the heliostat field and restriction parameters of the heliostat field facilities;

[0009] S2. Preprocessing environmental information and restriction parameters;

[0010] S3. Determine the shadow area and reflective area of ​​each heliostat; and determine the cutoff efficiency of the collector;

[0011] S4. Construct the NSGA-II optimization model, input the preprocessed environmental information, restriction parameters, shadow area of ​​the heliostat, luminous area and collector cutoff efficiency into the NSGA-II optimization model to obtain the heliostat field layout results, and display them through a visualization interface.

[0012] Furthermore, the environmental information includes the longitude and latitude of the target location where the heliostat field is arranged, as well as the altitude and light intensity.

[0013] Furthermore, the heliostat field facility restriction parameters include the absorption tower height, collector size and heliostat size in the heliostat field system.

[0014] Furthermore, preprocessing the environmental information and restriction parameters specifically includes:

[0015] Eliminate abnormal parameters from environmental information and restriction parameters.

[0016] Furthermore, the Monte Carlo ray tracing method and the plane projection method are used to calculate the shadow area and the reflection area of ​​each heliostat in the heliostat field.

[0017] Beneficial effects of the present invention: Through the present invention, by obtaining the environmental parameters and restriction parameters of the actual target position of the heliostat field, and determining the shadow area and reflection area of ​​each heliostat in the heliostat field, these parameters are input into the SA&NSGA-II algorithm model to obtain the optimal heliostat field structure parameters, thereby effectively improving the utilization rate of solar energy and the efficiency of solar power generation. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The present invention will be further described below in conjunction with the accompanying drawings and embodiments:

[0019] Figure 1 It is a flow chart of the present invention.

[0020] Figure 2 It is a schematic diagram of the heliostat field structure of the present invention.

[0021] Figure 3 for Figure 2Efficiency distribution diagram of the heliostat field system.

[0022] Figure 4 This is a schematic diagram of the optimized layout of the present invention.

[0023] Figure 5 This is a diagram of the output efficiency of the heliostat field after optimization according to the present invention. DETAILED DESCRIPTION

[0024] The present invention is further described in detail below:

[0025] The present invention provides a heliostat field optimization method based on a ray tracing model and an NSGA-II algorithm, comprising the following steps:

[0026] S1. Obtaining environmental information of the heliostat field and restriction parameters of the heliostat field facilities;

[0027] S2. Preprocessing environmental information and restriction parameters;

[0028] S3. Determine the shadow area and reflective area of ​​each heliostat; and determine the cutoff efficiency of the collector;

[0029] S4. Construct an NSGA-II optimization model (the English abbreviation for multi-objective genetic algorithm), input the preprocessed environmental information, restriction parameters, shadow area of ​​heliostat, luminous area and collector cutoff efficiency into the NSGA-II optimization model to obtain the heliostat field layout result, and display it through a visual interface. Through the above method, by obtaining the environmental parameters and restriction parameters of the actual target position of the heliostat field, and determining the shadow area and reflective area of ​​each heliostat in the heliostat field, these parameters are input into the SA&NSGA-II algorithm model to obtain the optimal heliostat field structure parameters, thereby effectively improving the utilization rate of solar energy and the efficiency of solar power generation.

[0030] In this embodiment, the environmental information includes the latitude and longitude of the target location for the heliostat field deployment, as well as the altitude and light intensity.

[0031] In this embodiment, the heliostat field facility restriction parameters include the absorption tower height, collector size, and heliostat size in the heliostat field system.

[0032] In this embodiment, preprocessing the environment information and restriction parameters specifically includes:

[0033] Eliminate abnormal parameters from environmental information and restriction parameters.

[0034] In this embodiment, the Monte Carlo ray tracing method and the plane projection method are used to calculate the shadow area and the reflection area of ​​each heliostat in the heliostat field.

[0035] Through the optimization of the invention, the specific results are as follows Figure 2-Figure 5 As shown, the effectiveness of the present invention is effectively demonstrated.

[0036] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solution of the present invention, which should be included in the scope of the claims of the present invention.

Claims

1. A heliostat field optimization method based on a ray tracing model and NSGA-II algorithm, characterized by: The following steps are involved: S1. Obtaining environmental information of the heliostat field and restriction parameters of the heliostat field facilities; S2. Preprocessing environmental information and restriction parameters; S3. Determine the shadow area and reflective area of ​​each heliostat; and determine the cutoff efficiency of the collector; S4. Construct the NSGA-II optimization model, input the preprocessed environmental information, restriction parameters, shadow area of ​​the heliostat, luminous area and collector cutoff efficiency into the NSGA-II optimization model to obtain the heliostat field layout results, and display them through a visualization interface.

2. The heliostat field optimization method based on the ray tracing model and the NSGA-II algorithm according to claim 1, characterized in that: The environmental information includes the latitude and longitude of the target location where the heliostat field is arranged, as well as the altitude and light intensity.

3. The heliostat field optimization method based on the ray tracing model and the NSGA-II algorithm according to claim 1, characterized in that: The heliostat field facility restriction parameters include the absorption tower height, collector size and heliostat size in the heliostat field system.

4. The heliostat field optimization method based on the ray tracing model and the NSGA-II algorithm according to claim 1, characterized in that: Preprocessing of environmental information and restriction parameters specifically includes: Eliminate abnormal parameters from environmental information and restriction parameters.

5. The heliostat field optimization method based on the ray tracing model and the NSGA-II algorithm according to claim 1, characterized in that: The Monte Carlo ray tracing method and plane projection method are used to calculate the shadow area and reflection area of ​​each heliostat in the heliostat field.

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