Distributed photovoltaic power generation optimization arrangement method and system

Abstract

The invention relates to the technical field of photovoltaic power generation, in particular to a distributed photovoltaic power generation optimization arrangement method and system. Photovoltaic panels are arranged in a three-dimensional pyramid form, a photovoltaic panel arrangement optimization problem is constructed, and a position model of the photovoltaic panels in a three-dimensional space is established; environment data is collected and analyzed, the built photovoltaic panel position model and the solar radiation energy absorption model are combined, the average solar total radiation quantity on the inclined plane is calculated, and the optimal photovoltaic panel installation mode is obtained. Compared with the traditional plane arrangement, the three-dimensional arrangement enables each photovoltaic panel to receive the maximum amount of direct and scattered solar radiation, the real-time data acquisition and analysis function responds to the environmental change in real time, the configuration of the photovoltaic panels is dynamically adjusted, and the energy capture is optimized. According to the method, manual intervention is reduced, the operation efficiency and reliability of the system are improved, the method is particularly suitable for being deployed in variable weather conditions and irregular terrains, and the adaptability and economic benefits of the photovoltaic system are greatly improved.

Description

Technical Field

[0001] The present invention relates to the technical field of photovoltaic power generation, and in particular to a distributed photovoltaic power generation optimization arrangement method and system. Background Art

[0002] Under the background of the rapid development of 5G technology, the construction of 5G base stations around the world is accelerating. At present, the number of 5G base stations in my country has reached nearly 1.6 million, and the network scale ranks among the top in the world. However, the energy supply problem of 5G base stations has become an important factor restricting its further development. Traditional 5G base stations mainly rely on power supply directly connected to the grid, which faces many challenges in remote areas or areas with complex geographical conditions, such as high cost and construction difficulty.

[0003] As the world pays more attention to environmental protection and sustainable development, the realization of the "dual carbon" goal has become a common pursuit of all walks of life. Exploring and utilizing clean and renewable energy, especially solar energy, has become a new research and application hotspot. As a mature way to utilize solar energy, the optimization design of photovoltaic power generation technology is particularly critical. Through innovative photovoltaic panel arrangement methods, such as the use of three-dimensional pyramid-shaped arrangement, the absorption efficiency of solar energy can be significantly improved, which not only helps to improve the energy output of photovoltaic power generation systems, but also reduces the floor space and enhances the system's adaptability to complex terrain.

[0004] Therefore, combining the high energy consumption characteristics of 5G base stations and the optimized development of photovoltaic technology, developing an independent energy supply system combined with a new photovoltaic panel arrangement method can not only provide 5G base stations with stable, economical and clean energy, but also help promote the optimization of energy structure and the realization of the "dual carbon" goals, which is of great significance for achieving wide coverage and efficient operation of 5G networks. Summary of the invention

[0005] In view of the above problems existing in the prior art, the present invention is proposed.

[0006] Therefore, the present invention provides a distributed photovoltaic power generation optimization arrangement method, which can solve the problem that traditional single-plane photovoltaic panels are affected by environmental factors. For example, in windy weather, traditional two-dimensional plane-mounted photovoltaic panels may be deformed and damaged. At the same time, single-plane photovoltaic panels occupy a large area in a limited space and have low space utilization. If they are installed in an overlapping manner, there may be obstruction, resulting in low photovoltaic power generation efficiency and other problems.

[0007] To solve the above technical problems, the present invention provides the following technical solutions: a distributed photovoltaic power generation optimization arrangement method, comprising: arranging photovoltaic panels in a three-dimensional pyramid shape, constructing a photovoltaic panel arrangement optimization problem and establishing a position model of photovoltaic panels in three-dimensional space; collecting sunshine data, combining the photovoltaic panel position model, real-time monitoring and optimizing photovoltaic panel data; combining the photovoltaic panel position model with the solar radiation energy absorption model, optimizing the combined model, and obtaining the optimal photovoltaic panel installation method by calculating the average monthly total solar radiation on the inclined surface.

[0008] As a preferred solution of the distributed photovoltaic power generation optimization arrangement method described in the present invention, the photovoltaic panel arrangement optimization problem includes: the photovoltaic panels are arranged in the form of a tetrahedron, the bottom surface of the tetrahedron is a rectangle, the length and width of the rectangle are represented by a and b respectively, the inclination angles of the four sides vary with the apex of the tetrahedron, the vertex coordinates of the tetrahedron are (x, y, z), and there is an optimal vertex that maximizes the total solar radiation absorbed by the four sides.

[0009] As a preferred embodiment of the distributed photovoltaic power generation optimization arrangement method described in the present invention, the establishment of the position model of the photovoltaic panel in the three-dimensional space includes taking O as the coordinate origin, setting the coordinates A (a, 0, 0), B (0, b, 0), C (a, b, 0) and P (x, y, z) in the three-dimensional coordinate system, and determining the optimal installation method of the photovoltaic panel by determining the position of the vertex P;

[0010] The plane vector formula for each face is expressed as,

[0011]

[0012] in, and are the plane vectors of different faces respectively;

[0013] The normal vector formula for each face is expressed as,

[0014]

[0015] Among them, i is the unit vector basis along the x-axis, j is the unit vector basis along the y-axis, and k is the unit vector basis along the z-axis. and are the normal vectors of different planes respectively;

[0016] The angle between each plane and the horizontal plane is expressed as follows:

[0017]

[0018] Among them, cosθ OAP 、cosθ OBP 、cosθBCP and cosθ ACP are the cosine values ​​of different angles respectively.

[0019] As a preferred solution of the distributed photovoltaic power generation optimization arrangement method described in the present invention, the real-time monitoring and optimization of photovoltaic panel data includes obtaining sunshine data from a meteorological station or a climate database, combining the three-dimensional position model of the photovoltaic panel, and collecting photovoltaic panel data through an irradiator;

[0020] The photovoltaic panel data includes the direct solar radiation on the horizontal surface and the scattered solar radiation on the horizontal surface. According to the changing characteristics of solar radiation, the actual data of photovoltaic panel data collection under several fixed time windows are obtained to establish an analysis set, and the average value and standard deviation of the actual data in the analysis set are comprehensively analyzed, and the data environment is divided into a normal data environment and an abnormal data environment. The average value threshold α and the standard deviation threshold β are set according to historical data, and the average value of the actual data in the analysis set is calculated to be σ, and the standard deviation is μ;

[0021] If σ≥α and μ<β, the data environment is judged to be a normal data environment. Based on real-time data and forecast analysis, the photovoltaic panel data is directly used as the raw data for calculating the average monthly solar radiation, and the cleaning and inspection frequency of the photovoltaic panels is optimized to maintain efficient operation.

[0022] If σ<α or μ≥β, the data environment is judged to be an abnormal data environment;

[0023] Analyze and optimize the data in the abnormal data environment. If σ<α and μ<β, the data environment is judged to be a persistent abnormal environment. Replace the location of the photovoltaic panels and data acquisition equipment, enhance the hardware protection of the system, change the arrangement of the photovoltaic panels, isolate the persistent abnormal data, and re-collect the photovoltaic panel performance data.

[0024] If σ≥α or σ<α and μ≥β, the data environment is judged to be a non-continuous abnormal environment, the specific cause of the data anomaly is determined, the abnormal data points are temporarily excluded, and repairs or adjustments are made.

[0025] As a preferred solution of the distributed photovoltaic power generation optimization arrangement method described in the present invention, the photovoltaic panel position model is combined with the solar radiation energy absorption model to include: the calculation method of the monthly average total solar radiation on the inclined surface of the photovoltaic module adopts the sky isotropic model, and the scattering and ground reflection have the same intensity in all directions. The calculation formula of the monthly average solar radiation on the inclined surface is expressed as:

[0026]

[0027] in, is the monthly average solar radiation on the inclined surface, is the monthly average solar radiation on the horizontal plane, is the monthly average direct solar radiation on the horizontal surface, is the monthly average solar diffuse radiation on the horizontal plane, is the ratio of the average direct solar radiation on the inclined surface to the horizontal surface, P g is the reflectivity of the ground surface, θ is the tilt angle of the photovoltaic panel, and cos is the cosine function.

[0028] The ratio of the average direct solar radiation of the inclined surface to the horizontal surface is calculated as follows:

[0029]

[0030] in, is the local latitude, δ is the solar declination angle, ω′ s is the sunset angle on the inclined surface of the photovoltaic module, ω s is the sunset angle on the horizontal plane, tan is the tangent function, sin is the sine function, and min is the minimum function.

[0031] As a preferred solution of the distributed photovoltaic power generation optimization arrangement method described in the present invention, wherein: the optimization calculation of the combined model includes that the area formula of each surface is expressed as:

[0032]

[0033] Among them, S1, S2, S3 and S4 are the areas of the photovoltaic panels on the four sides;

[0034] The amount of radiation absorbed by each photovoltaic panel is expressed as follows:

[0035]

[0036] in, and are the radiation absorbed by the four photovoltaic panels, and θ1, θ2, θ3 and θ4 are the tilt angles of the four photovoltaic panels.

[0037] As a preferred solution of the distributed photovoltaic power generation optimization arrangement method described in the present invention, the optimal photovoltaic panel installation method includes calculating the monthly average total solar radiation on the inclined surface, and the formula is expressed as follows:

[0038]

[0039] Find the extreme points where the partial derivatives of I with respect to x, y and z are 0, calculate the maximum value of the total irradiance, and obtain the optimal arrangement of the three-dimensional photovoltaic panel installation.

[0040] Another object of the present invention is to provide a distributed photovoltaic power generation optimization arrangement system. By introducing the arrangement and optimization of photovoltaic panels in the form of a three-dimensional pyramid, the present invention constructs a position model of photovoltaic panels in three-dimensional space, allowing the system to dynamically adjust the angle and position of photovoltaic panels according to real-time environmental data, thereby optimizing the absorption of solar radiation energy, calculating the monthly average total solar radiation on the inclined surface, and automatically determining the best installation method of photovoltaic panels. The method of the present invention provides a more efficient space utilization and energy management solution for photovoltaic power generation systems, which is particularly suitable for areas with limited space or complex environmental conditions.

[0041] As a preferred solution of a distributed photovoltaic power generation optimization arrangement system described in the present invention, it includes: a photovoltaic panel arrangement module, a data optimization module, and an energy calculation module;

[0042] The arrangement optimization module adopts a three-dimensional pyramid shape for arrangement, and adjusts the tilt angle of the photovoltaic panel by changing the position of the pyramid vertex to construct a photovoltaic panel arrangement optimization problem;

[0043] The data optimization module collects sunshine data, analyzes data quality in combination with the location model of the photovoltaic panels, and makes corresponding data adjustments and optimizations based on the mean and standard deviation of the data;

[0044] The energy calculation module combines the photovoltaic panel position model and the solar radiation energy absorption model to calculate the monthly average total solar radiation on the surface of each photovoltaic panel and optimize the position and arrangement of the photovoltaic panels.

[0045] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and wherein when the processor executes the computer program, the processor implements the steps of any one of the methods for optimizing the arrangement of distributed photovoltaic power generation.

[0046] A computer-readable storage medium having a computer program stored thereon, characterized in that when the computer program is executed by a processor, the steps of any one of the methods for optimizing the arrangement of distributed photovoltaic power generation are implemented.

[0047] Beneficial effects of the present invention: The present invention significantly improves the energy capture efficiency of the photovoltaic power generation system through an innovative three-dimensional pyramid-shaped photovoltaic panel arrangement. Compared with the traditional planar arrangement, the three-dimensional arrangement enables each photovoltaic panel to receive the maximum amount of direct and scattered solar radiation, thereby improving the overall energy efficiency of the system. The real-time data acquisition and analysis function of the present invention enables the system to respond to environmental changes instantly, dynamically adjust the configuration of photovoltaic panels, and optimize energy capture. The optimization function of the present invention not only reduces manual intervention and improves the operating efficiency and reliability of the system, but also enhances the adaptability and economic benefits of the photovoltaic system, providing new possibilities for green energy solutions. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0049] Figure 1 A schematic flow chart of a distributed photovoltaic power generation optimization arrangement method provided by an embodiment of the present invention.

[0050] Figure 2 A schematic diagram of the device structure of a distributed photovoltaic power generation optimization arrangement method provided by an embodiment of the present invention.

[0051] Figure 3 A module diagram of a distributed photovoltaic power generation optimization arrangement system provided for one embodiment of the present invention. DETAILED DESCRIPTION

[0052] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0053] Example 1, reference Figure 1-Figure 3 , which is the first embodiment of the present invention, provides a distributed photovoltaic power generation optimization arrangement method, comprising:

[0054] S1: Photovoltaic panels are arranged in a three-dimensional pyramid shape, the photovoltaic panel arrangement optimization problem is constructed, and the position model of photovoltaic panels in three-dimensional space is established.

[0055] Before describing the embodiments of the present invention in detail, for the sake of clarity, the preliminary research results of the present invention are first summarized.

[0056] With the deepening of new energy utilization technology and the gradual development and maturity of 5G technology, the survey found that the commonly used 5G power supply method is mainly switching power supply. The 5G base station AAU adopts Massive MIMO (massive multiple input multiple output) technology, which causes a significant increase in equipment power. The power loss of 5G base stations is about 3 to 4 times that of 4G base stations. At the same time, 5G base stations and existing base stations are built on the same site in large numbers, which brings great difficulties to the supporting power of base stations. If the original switching power supply is directly shared, it will bring problems such as insufficient switching power supply capacity and insufficient battery backup time. If a new switching power supply needs to be built or replaced, a lot of investment will be wasted. At the same time, different base stations have different power losses. How to find an independent power supply for 5G to solve the problem of insufficient switching power supply backup as a supplement to the switching power supply, and how 5G can reduce power loss are all problems that need to be solved when building 5G base stations. The power and size of 5G base station equipment are shown in Table 1.

[0057] Table 1. 5G base station equipment power and size table

[0058]

[0059] This paper studies a new spatial arrangement of photovoltaic panels in an independent photovoltaic power generation method to solve the 5G power supply problem of some equipment by combining source-energy storage-load cooperation.

[0060] It should be noted that, assuming that in a given limited three-dimensional space, the optimal spatial arrangement model of solar panels is established with the goal of obtaining the maximum power generation. According to the spatial arrangement model, a photovoltaic power generation system is constructed so that the system can absorb light energy to the maximum extent in the spatial arrangement. First, a spatial three-dimensional model of photovoltaic panels is constructed to study the power generation of the system.

[0061] The total solar energy I absorbed by the system is used to characterize its power generation. For this area, the illumination conditions in the area can be obtained from historical data. Therefore, when placed within a limited range in the area, the light energy absorbed by the photovoltaic solar panel per unit area is only determined by the inclination angle of the photovoltaic solar panel installation, that is, the angle between the photovoltaic panel and the ground. The formula for the light energy absorbed by the photovoltaic solar panel per unit area is expressed as,

[0062] y=g(θ)

[0063] Where y is the light energy absorbed per unit area and g is a function of the angle θ.

[0064] After the position is determined, a three-dimensional rectangular coordinate is established in space, and the vertex coordinates of the photovoltaic panel are P (x, y, z). The photovoltaic panel can be equivalent to the plane equation of a spatial plane photovoltaic panel, and the formula is expressed as follows:

[0065] ∑ax+by+cz+d=0

[0066] Among them, a, b, c and d are different parameters of the plane equation.

[0067] After the parameters are determined, the position of the photovoltaic panel can be determined. The installation inclination angle of the photovoltaic panel is a function of the plane equation parameters. The solar energy absorbed by the area of ​​the photovoltaic solar panel is a function of the plane equation parameters. The formula is expressed as:

[0068] y=g(θ)=g(a,b,c,d)

[0069] For the entire photovoltaic power generation system, the absorbed energy is calculated by surface integral, and the formula is expressed as:

[0070] I=∫∫∑g(a,b,c,d)ds=∫∫ ax+by+cz+d＝0 g(a,b,c,d)ds

[0071] At this point, the plane equation of the photovoltaic panel is unknown and is only determined as a spatial plane. At this point, the photovoltaic panel can be converted into a pure mathematical model.

[0072] It can be seen that the solar energy absorbed by the photovoltaic panel is four functions about the spatial plane, and the formula is expressed as follows:

[0073] I=I(a,b,c,d)

[0074] Taking partial derivatives of the parameters of I, we get a series of solutions.

[0075]

[0076] Where i is the photovoltaic panel plane index value.

[0077] By arranging and combining the solutions according to their rules and target requirements, a series of small planes can be determined, that is, the plane can be determined.

[0078] a i x+b i y+c i z+d i =0; (a i ,b i ,c i ,d i )

[0079] By splicing the above series of planes, a large planar photovoltaic power generation system can be obtained. Compared with ordinary planes, its characteristic is that it makes full use of one plane to convert it into multiple planes to improve the utilization rate of limited space.

[0080] Furthermore, the spatial stereoscopic model of the photovoltaic panels is further simplified, such as arranging the photovoltaic panels in a pyramid shape, which can be a triangular pyramid, a quadrangular pyramid, a pentagonal pyramid, etc. The photovoltaic panels arranged in a quadrangular pyramid are taken as an example for explanation. The photovoltaic panels are arranged in a quadrangular pyramid shape, and the bottom surface of the quadrangular pyramid is a rectangle. The length and width of the rectangle are represented by a and b respectively. The inclination angles of the four sides vary with the apex of the quadrangular pyramid. The coordinates of the vertex of the quadrangular pyramid are (x, y, z), and there is an optimal vertex that maximizes the total solar radiation absorbed by the four sides.

[0081] Further, such as Figure 2 As shown, the establishment of the position model of the photovoltaic panel in the three-dimensional space includes taking O as the coordinate origin, setting the coordinates A(a,0,0), B(0,b,0), C(a,b,0) and P(x,y,z) in the three-dimensional coordinate system, and determining the optimal installation method of the photovoltaic panel by determining the position of the vertex P;

[0082] The plane vector formula for each face is expressed as,

[0083]

[0084] in, and are the plane vectors of different faces respectively;

[0085] The normal vector formula for each face is expressed as,

[0086]

[0087]

[0088] Among them, i is the unit vector basis along the x-axis, j is the unit vector basis along the y-axis, and k is the unit vector basis along the z-axis. and are the normal vectors of different planes respectively;

[0089] The angle between each plane and the horizontal plane is expressed as follows:

[0090]

[0091] Among them, cosθ OAP 、cosθ OBP 、cosθ BCP and cosθ ACP are the cosine values ​​of different angles respectively.

[0092] S2: Collect sunshine data, combine it with the location model of photovoltaic panels, and monitor and optimize photovoltaic panel data in real time.

[0093] It should be noted that the real-time monitoring and optimization of photovoltaic panel data includes obtaining sunshine data from a weather station or a climate database, combining the three-dimensional position model of the photovoltaic panel, and collecting the photovoltaic panel data through an irradiator;

[0094] The photovoltaic panel data includes the direct solar radiation on the horizontal surface and the scattered solar radiation on the horizontal surface. According to the changing characteristics of solar radiation, the actual data of photovoltaic panel data collection under several fixed time windows are obtained to establish an analysis set, and the average value and standard deviation of the actual data in the analysis set are comprehensively analyzed, and the data environment is divided into a normal data environment and an abnormal data environment. The average value threshold α and the standard deviation threshold β are set according to historical data, and the average value of the actual data in the analysis set is calculated to be σ, and the standard deviation is μ;

[0095] If σ≥α and μ<β, the data environment is judged to be a normal data environment. Based on real-time data and forecast analysis, the photovoltaic panel data is directly used as the raw data for calculating the average monthly solar radiation, and the cleaning and inspection frequency of the photovoltaic panels is optimized to maintain efficient operation.

[0096] If σ<α or μ≥β, the data environment is judged to be an abnormal data environment;

[0097] Analyze and optimize the data in the abnormal data environment. If σ<α and μ<β, the data environment is judged to be a persistent abnormal environment. Replace the location of the photovoltaic panels and data acquisition equipment, enhance the hardware protection of the system, change the arrangement of the photovoltaic panels, isolate the persistent abnormal data, and re-collect the photovoltaic panel performance data.

[0098] If σ≥α or σ<α and μ≥β, the data environment is judged to be a non-continuous abnormal environment, the specific cause of the data anomaly is determined, the abnormal data points are temporarily excluded, and repairs or adjustments are made.

[0099] S3: Combine the photovoltaic panel position model with the solar radiation energy absorption model, optimize the combined model, and obtain the optimal photovoltaic panel installation method by calculating the monthly average total solar radiation on the inclined surface.

[0100] It should be noted that the photovoltaic panel position model is combined with the solar radiation energy absorption model, and the calculation method of the monthly average total solar radiation on the inclined surface of the photovoltaic module adopts the sky isotropic model, and the scattering and ground reflection have the same intensity in all directions. The calculation formula of the monthly average solar radiation on the inclined surface is expressed as:

[0101]

[0102] in, is the monthly average solar radiation on the inclined surface, is the monthly average solar radiation on the horizontal plane, is the monthly average direct solar radiation on the horizontal surface, is the monthly average solar diffuse radiation on the horizontal plane, is the ratio of the average direct solar radiation on the inclined surface to the horizontal surface, P g is the reflectivity of the ground surface, θ is the tilt angle of the photovoltaic panel, and cos is the cosine function.

[0103] The ratio of the average direct solar radiation of the inclined surface to the horizontal surface is calculated as follows:

[0104]

[0105] in, is the local latitude, δ is the solar declination angle, ω′ s is the sunset angle on the inclined surface of the photovoltaic module, ω s is the sunset angle on the horizontal plane, tan is the tangent function, sin is the sine function, and min is the minimum function.

[0106] It should be noted that the optimization calculation of the combined model includes that the area formula of each face is expressed as:

[0107]

[0108] Among them, S1, S2, S3 and S4 are the areas of the photovoltaic panels on the four sides;

[0109] The amount of radiation absorbed by each photovoltaic panel is expressed as follows:

[0110]

[0111] in, and are the radiation absorbed by the four photovoltaic panels, and θ1, θ2, θ3 and θ4 are the tilt angles of the four photovoltaic panels.

[0112] It should be noted that the optimal photovoltaic panel installation method includes calculating the monthly average total solar radiation on the inclined surface, which is expressed as follows:

[0113]

[0114] Find the extreme points where the partial derivatives of I with respect to x, y and z are 0, calculate the maximum value of the total irradiance, and obtain the optimal arrangement of the three-dimensional photovoltaic panel installation.

[0115] The above is a schematic scheme of a distributed photovoltaic power generation optimization arrangement method of this embodiment. It should be noted that the technical scheme of the distributed photovoltaic power generation optimization arrangement system and the technical scheme of the above-mentioned distributed photovoltaic power generation optimization arrangement method belong to the same concept. For details not described in detail in the technical scheme of the distributed photovoltaic power generation optimization arrangement system in this embodiment, please refer to the description of the technical scheme of the above-mentioned distributed photovoltaic power generation optimization arrangement method.

[0116] like Figure 3 As shown, the distributed photovoltaic power generation optimization arrangement system in this embodiment includes: a photovoltaic panel arrangement module, a data optimization module, and an energy calculation module;

[0117] The arrangement optimization module adopts a three-dimensional pyramid shape for arrangement, and adjusts the tilt angle of the photovoltaic panel by changing the position of the pyramid vertex;

[0118] The data optimization module collects sunshine data, analyzes data quality in combination with the location model of the photovoltaic panels, and makes corresponding data adjustments and optimizations based on the mean and standard deviation of the data;

[0119] The energy calculation module combines the photovoltaic panel position model and the solar radiation energy absorption model to calculate the monthly average total solar radiation on the surface of each photovoltaic panel and optimize the position and arrangement of the photovoltaic panels.

[0120] This embodiment further provides a computing device, which is applicable to the case of the distributed photovoltaic power generation optimization arrangement method, including:

[0121] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.

[0122] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0123] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0124] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0125] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. 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 solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A distributed photovoltaic power generation optimization arrangement method, characterized by: include, Photovoltaic panels are arranged in a three-dimensional pyramid shape, the photovoltaic panel arrangement optimization problem is constructed, and the position model of photovoltaic panels in three-dimensional space is established; Collect sunshine data, combine it with the location model of photovoltaic panels, and monitor and optimize photovoltaic panel data in real time; The photovoltaic panel position model is combined with the solar radiation energy absorption model, and the combined model is optimized and calculated. The optimal photovoltaic panel installation method is obtained by calculating the monthly average total solar radiation on the inclined surface.

2. A distributed photovoltaic power generation optimization arrangement method as claimed in claim 1, characterized in that: The photovoltaic panel arrangement optimization problem is constructed, the photovoltaic panels are arranged in the form of a tetrahedron, the bottom surface of the tetrahedron is a rectangle, the length and width of the rectangle are represented by a and b respectively, the inclination angles of the four sides vary with the apex of the tetrahedron, the vertex coordinates of the tetrahedron are (x, y, z), and there is an optimal vertex that maximizes the total solar radiation absorbed by the four sides.

3. A distributed photovoltaic power generation optimization arrangement method as claimed in claim 2, characterized in that: The establishing of the position model of the photovoltaic panel in the three-dimensional space includes taking O as the coordinate origin, setting coordinates A (a, 0, 0), B (0, b, 0), C (a, b, 0) and P (x, y, z) in the three-dimensional coordinate system, and determining the optimal installation method of the photovoltaic panel by determining the position of the vertex P; The plane vector formula for each face is expressed as, in, and are the plane vectors of different faces respectively; The normal vector formula for each face is expressed as, Among them, i is the unit vector basis along the x-axis, j is the unit vector basis along the y-axis, and k is the unit vector basis along the z-axis. and are the normal vectors of different planes respectively; The angle between each plane and the horizontal plane is expressed as follows: Among them, cosθ OAP 、cosθ OBP 、cosθ BCP and cosθ ACP are the cosine values ​​of different angles respectively.

4. A distributed photovoltaic power generation optimization arrangement method as claimed in claim 3, characterized in that: The real-time monitoring and optimization of photovoltaic panel data includes obtaining sunshine data from a weather station or a climate database, combining the three-dimensional position model of the photovoltaic panel, and collecting the photovoltaic panel data through a irradiator; The photovoltaic panel data includes the direct solar radiation on the horizontal surface and the scattered solar radiation on the horizontal surface. According to the changing characteristics of solar radiation, the actual data of photovoltaic panel data collection under several fixed time windows are obtained to establish an analysis set, and the average value and standard deviation of the actual data in the analysis set are comprehensively analyzed, and the data environment is divided into a normal data environment and an abnormal data environment. The average value threshold α and the standard deviation threshold β are set according to historical data, and the average value of the actual data in the analysis set is calculated to be σ, and the standard deviation is μ; If σ≥α and μ<β, the data environment is judged to be a normal data environment. Based on real-time data and forecast analysis, the photovoltaic panel data is directly used as the raw data for calculating the average monthly solar radiation, and the cleaning and inspection frequency of the photovoltaic panels is optimized to maintain efficient operation. If σ<α or μ≥β, the data environment is judged to be an abnormal data environment; Analyze and optimize the data in the abnormal data environment. If σ<α and μ<β, the data environment is judged to be a persistent abnormal environment. Replace the location of the photovoltaic panels and data acquisition equipment, enhance the hardware protection of the system, change the arrangement of the photovoltaic panels, isolate the persistent abnormal data, and re-collect the photovoltaic panel performance data. If σ≥α or σ<α and μ≥β, the data environment is judged to be a non-continuous abnormal environment, the specific cause of the data anomaly is determined, the abnormal data points are temporarily excluded, and repairs or adjustments are made.

5. A distributed photovoltaic power generation optimization arrangement method as claimed in claim 4, characterized in that: The photovoltaic panel position model is combined with the solar radiation energy absorption model, and the calculation method of the monthly average total solar radiation on the inclined surface of the photovoltaic module adopts the sky isotropic model, and the scattering and ground reflection have the same intensity in all directions. The calculation formula of the monthly average solar radiation on the inclined surface is expressed as: in, is the monthly average solar radiation on the inclined surface, is the monthly average solar radiation on the horizontal plane, is the monthly average direct solar radiation on the horizontal surface, is the monthly average solar diffuse radiation on the horizontal plane, is the ratio of the average direct solar radiation on the inclined surface to the horizontal surface, P g is the reflectivity of the ground surface, θ is the tilt angle of the photovoltaic panel, and cos is the cosine function. The ratio of the average direct solar radiation of the inclined surface to the horizontal surface is calculated as follows: in, is the local latitude, δ is the solar declination angle, ω s is the sunset angle on the inclined surface of the photovoltaic module, ω s is the sunset angle on the horizontal plane, tan is the tangent function, sin is the sine function, and min is the minimum function.

6. A distributed photovoltaic power generation optimization arrangement method as claimed in claim 5, characterized in that: The optimization calculation of the combined model includes that the area formula of each face is expressed as: Among them, S1, S2, S3 and S4 are the areas of the photovoltaic panels on the four sides; The amount of radiation absorbed by each photovoltaic panel is expressed as follows: in, and are the radiation absorbed by the four photovoltaic panels, and θ1, θ2, θ3 and θ4 are the tilt angles of the four photovoltaic panels.

7. A distributed photovoltaic power generation optimization arrangement method as claimed in claim 6, characterized in that: The optimal photovoltaic panel installation method includes calculating the monthly average total solar radiation on the inclined surface, which is expressed as follows: Find the extreme points where the partial derivatives of I with respect to x, y and z are 0, calculate the maximum value of the total irradiance, and obtain the optimal arrangement of the three-dimensional photovoltaic panel installation.

8. A system based on a distributed photovoltaic power generation optimization arrangement method according to any one of claims 1 to 7, characterized in that: Including photovoltaic panel arrangement module, data optimization module, and energy calculation module; The arrangement optimization module adopts a three-dimensional pyramid shape for arrangement, and adjusts the tilt angle of the photovoltaic panel by changing the position of the pyramid vertex to construct a photovoltaic panel arrangement optimization problem; The data optimization module collects sunshine data, analyzes data quality in combination with the location model of the photovoltaic panels, and makes corresponding data adjustments and optimizations based on the mean and standard deviation of the data; The energy calculation module combines the photovoltaic panel position model and the solar radiation energy absorption model to calculate the monthly average total solar radiation on the surface of each photovoltaic panel and optimize the position and arrangement of the photovoltaic panels.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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