Photovoltaic inclination angle optimization method and device for tea-light complementary project, and storage medium

Abstract

The invention relates to a photovoltaic inclination angle optimization method and device for a tea-light complementary project and a storage medium, and the method comprises the steps: S1, obtaining construction parameters of a tea garden photovoltaic array and meteorological parameters of a construction site, and building a photovoltaic array power generation amount model and a photovoltaic array radiation amount model; s2, based on a photovoltaic array power generation amount model, obtaining a mapping relation of power generation income P1 with respect to a photovoltaic panel inclination angle; s3, based on the photovoltaic array radiation quantity model, obtaining a mapping relation of the radiation quantity with respect to the inclination angle of the photovoltaic panel; s4, based on the mapping relation of the radiation quantity with respect to the inclination angle of the photovoltaic panel, obtaining the mapping relation of the first characteristic value P2 with respect to the inclination angle of the photovoltaic panel; s5, superposing the power generation income and the inclination angle of the photovoltaic panel to serve as an optimization target P, and obtaining a mapping relation of the optimization target P with respect to the inclination angle of the photovoltaic panel; and S6, determining an optimal photovoltaic panel inclination angle. Compared with the prior art, the method has the advantages of improving the acquisition speed of the optimal dip angle of the photovoltaic panel and the like.

Description

Technical Field

[0001] The invention relates to the field of tea garden photovoltaics, and in particular to a photovoltaic tilt angle optimization method, device and storage medium for a tea-photovoltaic complementary project. Background Art

[0003] Considering that tea is a shade-loving plant, the combination of agriculture and light will inevitably increase the total income per unit area. Therefore, the combination of photovoltaics and tea gardens can not only reduce the area occupied by laying photovoltaic panels, but also increase the output per unit area of ​​land.

[0004] In 2018, the College of Agriculture of Zhejiang University conducted relevant research on photovoltaic tea gardens. They used PVsyst to simulate the power generation of photovoltaic panels, used Rhino to simulate the distribution of solar radiation under photovoltaic panels, and conducted field experiments and sampling, and concluded that the quality of tea in photovoltaic tea gardens is better than that in open-air tea gardens. In addition, the team also optimized the spacing of photovoltaic panels and initially achieved tea-light complementarity. However, the team has not yet been able to determine the optimal tilt angle of photovoltaic panels, and further research is needed.

[0005] In November 2021, Huaneng and Guizhou University built a photovoltaic tea garden experimental site in Duyunba, Qiannan. "Fuding Dabai" was selected as the first batch of experimental subjects, and photovoltaic panels with different inclinations and heights were built above the tea leaves. After a whole year of experiments, photovoltaic tea has achieved an improvement in tea quality. Among them, the highest control group tea increased theanine content by 40%, and the amino acid content reached 9%. Building photovoltaic panels in the tea garden not only improves the freshness of the tea but also reduces the bitterness, greatly improving the economic benefits of the tea. In addition, the output of the tea garden has not decreased, and the final tea output has increased by more than 50%. In addition to the tea revenue, the annual power generation of solar panels in the experimental site has reached 500,000 kWh, reducing carbon emissions by 50 tons per year. The total photovoltaic revenue per unit area has been able to exceed the sum of the open-air tea garden and solar panels of the same area. However, the photovoltaic panel bracket in this study is a fixed bracket, which cannot be adjusted according to the requirements, and the adjustment method to increase the revenue of the photovoltaic panel was not considered in this experiment, and the balance between photovoltaic revenue and tea revenue was not achieved.

[0006] Although the feasibility of existing technologies for tea-light coupling projects has been verified, the optimal tilt angle of photovoltaic panels has not yet been determined, resulting in limited utilization of radiation. Summary of the invention

[0007] The purpose of the present invention is to provide a photovoltaic tilt angle optimization method, device and storage medium for a tea-light complementary project.

[0008] The purpose of the present invention can be achieved by the following technical solutions:

[0009] A photovoltaic tilt angle optimization method for a tea-light complementary project, comprising:

[0010] Step S1: Obtain the construction parameters of the tea garden photovoltaic array and the meteorological parameters of the construction site, and build a photovoltaic array power generation model and a photovoltaic array radiation model respectively;

[0011] Step S2: Based on the photovoltaic array power generation model, a mapping relationship between the power generation income P1 and the photovoltaic panel inclination angle is obtained;

[0012] Step S3: based on the photovoltaic array radiation model, obtaining a mapping relationship between the radiation at a first set height below the photovoltaic panel and the photovoltaic panel inclination angle;

[0013] Step S4: Based on the mapping relationship between the radiation amount at the first set height below the photovoltaic panel and the photovoltaic panel inclination angle, combined with the mapping relationship between the first eigenvalue P2 and the radiation amount, a mapping relationship between the first eigenvalue P2 and the photovoltaic panel inclination angle is obtained;

[0014] Step S5: superimposing the power generation income and the photovoltaic panel inclination angle as the optimization target P, and obtaining a mapping relationship between the optimization target P and the photovoltaic panel inclination angle;

[0015] Step S6: Determine the optimal photovoltaic panel inclination angle based on the mapping relationship between the optimization target P and the photovoltaic panel inclination angle.

[0016] The meteorological parameters include horizontal radiation, diffuse horizontal radiation, and atmospheric turbidity factor;

[0017] The construction parameters are obtained based on the construction drawings, including the size of the photovoltaic panels, the spacing between the photovoltaic panels, the relative positions between the photovoltaic arrays, the vertical height of the photovoltaic panels, the geographical location of the photovoltaic tea garden, the power of the photovoltaic panels and the inverter parameters.

[0018] The photovoltaic array power generation model is built based on PVsyst, and the photovoltaic array radiation model is built based on Rhino.

[0019] The first set height is the height of the tea tree canopy.

[0020] The step S2 comprises:

[0021] Step S2-1: randomly generating a plurality of tilt angle simulation values ​​within a first set range;

[0022] Step S2-2: Based on the photovoltaic array power generation model, the photovoltaic power generation at each tilt angle simulation value in each month is obtained respectively;

[0023] Step S2-3: Based on the obtained photovoltaic power generation at each inclination angle simulation value in each month, a mapping relationship between the power generation corresponding to each month and the photovoltaic panel inclination angle is fitted:

[0024] W m =w_solar m (θ)

[0025] Where: W m is the power generation in month m, θ is the inclination angle of the photovoltaic panel;

[0026] Step S2-4: Based on the function of the power generation in each month, combined with the on-grid electricity price, terminal electricity price and average electricity consumption of the tea garden in each month, the mapping relationship between the power generation income P1 and the photovoltaic panel inclination angle corresponding to each month is obtained.

[0027] The step S3 comprises:

[0028] Step S3-1: Importing a first set height;

[0029] Step S3-2: Based on the photovoltaic array power generation model, the radiation amount at the first set height below the photovoltaic panel at each tilt angle simulation value in each month is obtained respectively;

[0030] Step S3-3: Based on the obtained radiation at the first set height below the photovoltaic panel at each inclination angle simulation value in each month, a mapping relationship between the radiation corresponding to each month and the inclination angle of the photovoltaic panel is fitted:

[0031] rad m =rad_solar m (θ)

[0032] Among them: rad m is the radiation at the first set height below the photovoltaic panel in month m.

[0033] The step S4 is specifically as follows:

[0034] Based on the mapping relationship between the radiation at the first set height below the photovoltaic panel in each month and the inclination angle of the photovoltaic panel, combined with the mapping relationship between the first eigenvalue P2 and the radiation, the mapping relationship between the first eigenvalue P2 and the inclination angle of the photovoltaic panel in each month is obtained.

[0035] The power generation income is:

[0036] P1=max((W m -Q m ),0)*pie 1,m +min(W m ,Q m )*pie 2,m

[0037] Where: Q m is the electricity consumption of the tea garden in month m, pie 1,m is the terminal electricity price in month m, pie 2,m is the on-grid electricity price in month m.

[0038] In step S6, a linear search method is used to obtain the photovoltaic panel inclination angle when the optimization target is maximum.

[0039] A photovoltaic tilt angle optimization device for a tea-light complementary project includes a memory, a processor, and a program stored in the memory, and the processor implements the above-mentioned method when executing the program.

[0040] A storage medium stores a program, which implements the above method when executed.

[0041] Compared with the prior art, the present invention has the following beneficial effects:

[0042] 1. The photovoltaic array power generation model and the photovoltaic array radiation model were established respectively, so as to simulate the power generation and the radiation below respectively. According to the obtained power generation and radiation, combined with the relationship between the relevant first eigenvalue and the radiation, the mapping relationship of the optimization target P on the inclination angle of the photovoltaic panel was obtained, so that the optimal inclination angle of the photovoltaic panel can be quickly determined.

[0043] 2. Meteorological parameters include horizontal radiation, diffuse horizontal radiation, and atmospheric turbidity factor. Construction parameters are obtained based on construction drawings, including photovoltaic panel size, photovoltaic panel spacing, relative position between photovoltaic arrays, photovoltaic panel vertical height, geographical location of photovoltaic tea garden, photovoltaic panel power and inverter parameters. The data is more comprehensive, so accurate simulation data can be obtained without actual measured data.

[0044] 3. The photovoltaic array power generation model is built based on PVsyst, and the photovoltaic array radiation model is built based on Rhino to reduce implementation costs.

[0045] 4. Obtain point values ​​based on randomly generated inclination simulation values, perform fitting, and establish mapping relationships according to months, thereby improving accuracy and efficiency in obtaining mapping relationships. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 It is a schematic flow chart of the main steps of the method of the present invention;

[0047] Figure 2 This is a schematic diagram of the fitting results of power generation, angle and month;

[0048] Figure 3 This is a 3D image of a photovoltaic panel built in Rhino7;

[0049] Figure 4 This is a schematic diagram of the simulated area under the photovoltaic panel support;

[0050] Figure 5 Function graph of optimization target and photovoltaic panel inclination angle. DETAILED DESCRIPTION

[0051] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. This embodiment is implemented based on the technical solution of the present invention, and provides a detailed implementation method and specific operation process, but the protection scope of the present invention is not limited to the following embodiments.

[0052] A photovoltaic tilt optimization method for tea-light complementary projects, such as Figure 1 As shown, including:

[0053] Step S1: Obtain the construction parameters of the tea garden photovoltaic array and the meteorological parameters of the construction site, and build a photovoltaic array power generation model and a photovoltaic array radiation model respectively;

[0054] Generally, meteorological parameters include horizontal radiation, diffuse horizontal radiation, and atmospheric turbidity factor;

[0055] The construction parameters can be obtained based on the construction drawings, and generally include the size of the photovoltaic panels, the spacing between the photovoltaic panels, the relative position between the photovoltaic arrays, the vertical height of the photovoltaic panels, the geographical location of the photovoltaic tea garden, the power of the photovoltaic panels, and the inverter parameters.

[0056] In this embodiment, the photovoltaic array power generation model is built based on PVsyst. Specifically, photovoltaic modules matching the project are selected in PVsyst, and a three-dimensional model of the photovoltaic array is established to take into account the factors of mutual shading of photovoltaic panels, so as to obtain photovoltaic benefits at different angles.

[0057] In this embodiment, the photovoltaic array radiation model is built based on Rhino. Specifically, a photovoltaic array model is built in Rhino, the rotation center of the photovoltaic array is determined, and the Ladybug plug-in is used to simulate the radiation at a height of the tea tree canopy plane under the panel. When building the photovoltaic model in Rhino, the photovoltaic panel is set to face south. Since the shading area of ​​the bracket is relatively small, the impact of the bracket on the radiation is ignored. Compare the panel placement in the construction drawing to conduct full-scale modeling of the tea garden photovoltaic panel, such as Figure 3 .

[0058] Import the meteorological data of the experimental site through DownloadRPW battery, set the start time of AnalysisPeriod to 6:00 and the end time to 18:00, and set the months to be simulated respectively. Figure 4 .

[0059] Step S2: Based on the photovoltaic array power generation model, a mapping relationship between the power generation income P1 and the photovoltaic panel inclination angle is obtained. Step S2 includes:

[0060] Step S2-1: randomly generating a plurality of tilt angle simulation values ​​within a first set range;

[0061] Step S2-2: Based on the photovoltaic array power generation model, the photovoltaic power generation at each tilt angle simulation value in each month is obtained respectively;

[0062] Step S2-3: Based on the obtained photovoltaic power generation at each inclination angle simulation value in each month, a mapping relationship between the power generation corresponding to each month and the photovoltaic panel inclination angle is fitted:

[0063] W m =w_solar m (θ)

[0064] Where: W m is the power generation in month m, θ is the inclination angle of the photovoltaic panel;

[0065] Step S2-4: Based on the function of the power generation in each month, combined with the on-grid electricity price, terminal electricity price and average electricity consumption of the tea garden in each month, the mapping relationship between the power generation income P1 and the photovoltaic panel inclination angle corresponding to each month is obtained.

[0066] In this embodiment, the photovoltaic power station uses three types of photovoltaic brackets, namely flexible photovoltaic brackets, fixed brackets, and tracking brackets, and the models of solar panels are also different. Three different photovoltaic arrays are built in PVsyst, and. Meteorological data from Meteonorm is used. The month is changed while adjusting the angle. The photovoltaic array power generation from 0 degrees to 50 degrees, from January to December is collected. Table 1 shows the simulated power generation data at different angles in some months.

[0067] Table 1

[0068]

[0069] After loading the data in Table 1 into MATLAB, fit it with a quadratic function of three variables, such as Figure 2 , the fitting result is a quadratic function,

[0070] Among them, in this embodiment, the power generation income is:

[0071] P1=max((W m -Q m ),0)*pie 1,m +min(W m ,Q m )*pie 2,m

[0072] Where: Q m is the electricity consumption of the tea garden in month m, pie 1,m is the terminal electricity price in month m, pie 2,m is the on-grid electricity price in month m.

[0073] Of course, in other embodiments, the revenue may be directly calculated using a single on-grid electricity price.

[0074] Step S3: Based on the photovoltaic array radiation model, a mapping relationship between the radiation at a first set height below the photovoltaic panel and the photovoltaic panel inclination angle is obtained, including:

[0075] Step S3-1: importing a first set height, the first set height being the height of the tea tree canopy;

[0076] Step S3-2: Based on the photovoltaic array power generation model, the radiation amount at the first set height below the photovoltaic panel at each tilt angle simulation value in each month is obtained respectively;

[0077] Step S3-3: Based on the obtained radiation at the first set height below the photovoltaic panel at each inclination angle simulation value in each month, a mapping relationship between the radiation corresponding to each month and the inclination angle of the photovoltaic panel is fitted:

[0078] rad m =rad_solar m (θ)

[0079] Among them: rad m is the radiation at the first set height below the photovoltaic panel in month m.

[0080] In addition, in this embodiment, the meteorological data of the experimental site is imported by DownloadRPW battery, the start time in AnalysisPeriod is set to 6 o'clock, the end time is set to 18 o'clock, and the months to be simulated are set respectively. The radiation amount in the rectangular space with a height of 0.9m under the photovoltaic panel is simulated, where the rectangle selects the axis of the adjacent bracket as the front and rear boundaries, and the photovoltaic panel bracket is used as the left and right boundaries of the simulated radiation plane. Figure 4 .

[0081] By adjusting the time period in the battery and continuously rotating the photovoltaic panel, the radiation conditions on its surface are counted.

[0082] Step S4: Based on the mapping relationship between the radiation at the first set height below the photovoltaic panel and the photovoltaic panel inclination angle, combined with the mapping relationship between the first eigenvalue P2 and the radiation, the mapping relationship between the first eigenvalue P2 and the photovoltaic panel inclination angle is obtained, specifically:

[0083] Based on the mapping relationship between the radiation at the first set height below the photovoltaic panel in each month and the inclination angle of the photovoltaic panel, combined with the mapping relationship between the first eigenvalue P2 and the radiation, the mapping relationship between the first eigenvalue P2 and the inclination angle of the photovoltaic panel in each month is obtained.

[0084] The first characteristic value P2 is specifically a quality parameter of tea leaves corresponding to different radiation amounts.

[0085] Step S5: superimposing the power generation income and the photovoltaic panel inclination angle as the optimization target P, and obtaining a mapping relationship between the optimization target P and the photovoltaic panel inclination angle;

[0086] Step S6: Determine the optimal photovoltaic panel inclination angle based on the mapping relationship between the optimization target P and the photovoltaic panel inclination angle. In this process, a linear search method is used to obtain the photovoltaic panel inclination angle when the optimization target is maximum, specifically to obtain the optimal photovoltaic panel inclination angle for each month.

[0087] The optimization target P can be understood as the total revenue of the tea-light system. After coupling the corresponding month's function through MATLAB, the functional relationship between the total revenue and the inclination angle of the photovoltaic panel in the final tea-light complementary mode can be obtained. The function of the total revenue and inclination angle of the tea-light coupling project is plotted. See Figure 5 The corresponding photovoltaic panel inclination angle for maximum benefit is obtained, see Table 2.

[0088] month Maximum total revenue Optimum inclination angle / degree January 5733.376682 35.01002 February 6952.752043 28.316633 March 9641.156073 22.965932 April 12447.88022 28.136273 May 13955.16927 31.022044 June 12303.78559 32.645291 July 13917.45998 30.300601 August 13935.82307 30.661323 September 11716.56443 10.000000 October 9492.488037 10.000000 November 6526.957031 36.673347 December 4457.903936 33.366733

[0089] Through calculation, the tea revenue of the flexible adjustable bracket in the tea-light complementary mode is 120% of the unobstructed tea revenue, and the photovoltaic revenue is 94.9% of the photovoltaic revenue under the condition of no tea. The purpose of harvesting both tea and light can be achieved.

[0090] If the above 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 method 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 code.

Claims

1. A photovoltaic tilt optimization method for a tea-light complementary project, characterized in that: include: Step S1: Obtain the construction parameters of the tea garden photovoltaic array and the meteorological parameters of the construction site, and build a photovoltaic array power generation model and a photovoltaic array radiation model respectively; Step S2: Based on the photovoltaic array power generation model, a mapping relationship between the power generation income P1 and the photovoltaic panel inclination angle is obtained; Step S3: based on the photovoltaic array radiation model, obtaining a mapping relationship between the radiation at a first set height below the photovoltaic panel and the photovoltaic panel inclination angle; Step S4: based on the mapping relationship between the radiation amount at the first set height below the photovoltaic panel and the photovoltaic panel inclination angle, combined with the mapping relationship between the first eigenvalue P2 and the radiation amount, a mapping relationship between the first eigenvalue P2 and the photovoltaic panel inclination angle is obtained; Step S5: superimposing the power generation income and the photovoltaic panel inclination angle as the optimization target P, and obtaining a mapping relationship between the optimization target P and the photovoltaic panel inclination angle; Step S6: Determine the optimal photovoltaic panel inclination angle based on the mapping relationship between the optimization target P and the photovoltaic panel inclination angle.

2. The photovoltaic tilt angle optimization method for a tea-light complementary project according to claim 1 is characterized in that: The meteorological parameters include horizontal radiation, diffuse horizontal radiation, and atmospheric turbidity factor; The construction parameters are obtained based on the construction drawings, including the size of the photovoltaic panels, the spacing between the photovoltaic panels, the relative position between the photovoltaic arrays, the vertical height of the photovoltaic panels, the geographical location of the photovoltaic tea garden, the power of the photovoltaic panels and the inverter parameters.

3. The photovoltaic tilt angle optimization method for a tea-light complementary project according to claim 1 is characterized in that: The photovoltaic array power generation model is built based on PVsyst, and the photovoltaic array radiation model is built based on Rhino.

4. The photovoltaic tilt angle optimization method for a tea-light complementary project according to claim 1 is characterized in that: The first set height is the height of the tea tree canopy.

5. The photovoltaic tilt angle optimization method for a tea-light complementary project according to claim 1 is characterized in that: The step S2 comprises: Step S2-1: randomly generating a plurality of tilt angle simulation values ​​within a first set range; Step S2-2: Based on the photovoltaic array power generation model, the photovoltaic power generation at each tilt angle simulation value in each month is obtained respectively; Step S2-3: Based on the obtained photovoltaic power generation at each inclination angle simulation value in each month, a mapping relationship between the power generation corresponding to each month and the photovoltaic panel inclination angle is fitted: IN m =w_solar m (θ) Where: W m is the power generation in month m, θ is the inclination angle of the photovoltaic panel; Step S2-4: Based on the function of the power generation in each month, combined with the on-grid electricity price, terminal electricity price and average electricity consumption of the tea garden in each month, the mapping relationship between the power generation income P1 and the photovoltaic panel inclination angle corresponding to each month is obtained.

6. The photovoltaic tilt angle optimization method for a tea-light complementary project according to claim 5 is characterized in that: The step S3 comprises: Step S3-1: Importing a first set height; Step S3-2: Based on the photovoltaic array power generation model, the radiation amount at the first set height below the photovoltaic panel at each tilt angle simulation value in each month is obtained respectively; Step S3-3: Based on the obtained radiation at the first set height below the photovoltaic panel at each inclination angle simulation value in each month, a mapping relationship between the radiation corresponding to each month and the inclination angle of the photovoltaic panel is fitted: wheel m =rad_solar m (θ) Among them: rad m is the radiation at the first set height below the photovoltaic panel in month m.

7. The photovoltaic tilt angle optimization method for a tea-light complementary project according to claim 6 is characterized in that: The step S4 is specifically as follows: Based on the mapping relationship between the radiation at the first set height below the photovoltaic panel in each month and the inclination angle of the photovoltaic panel, combined with the mapping relationship between the first eigenvalue P2 and the radiation, the mapping relationship between the first eigenvalue P2 and the inclination angle of the photovoltaic panel in each month is obtained.

8. The photovoltaic tilt angle optimization method for a tea-light complementary project according to claim 1 is characterized in that: In step S6, a linear search method is used to obtain the photovoltaic panel inclination angle when the optimization target is maximum.

9. A photovoltaic tilt optimization device for a tea-light complementary project, comprising a memory, a processor, and a program stored in the memory, characterized in that: When the processor executes the program, the method according to any one of claims 1 to 8 is implemented.

10. A storage medium having a program stored thereon, characterized in that: When the program is executed, the method according to any one of claims 1 to 8 is implemented.

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