Photovoltaic rack control method and related device

Abstract

The application discloses a photovoltaic support control method and related device, relates to the photovoltaic power generation technical field, generates multiple candidate tracking angles in the physical limiting range of the tracking support, corrects the ground average irradiance corresponding to each candidate tracking angle according to the light saturation characteristic and the light inhibition characteristic of crops, obtains the effective photosynthetic irradiance corresponding to each candidate tracking angle, carries out hierarchical screening operation on the multiple candidate tracking angles based on the shading rate constraint condition of crops, the segmented electricity price tolerance function, the effective photosynthetic irradiance corresponding to each candidate tracking angle and the total irradiance of the component surface, obtains the target tracking angle, generates the control instruction including the target tracking angle, and drives the tracking support to rotate according to the target tracking angle. That is, when the tracking angle of the tracking support is determined, the shading condition and the irradiance of crops are comprehensively considered, so that the purposes of photovoltaic power generation and crop light supply are simultaneously considered.

Description

Technical Field

[0001] This application relates to the field of photovoltaic power generation technology, and in particular to a photovoltaic support control method and related device. Background Technology

[0002] Currently, photovoltaic power generation is widely used. Taking agro-photovoltaic integration as an example, it is a land use model that integrates photovoltaic power generation and agricultural production on the same piece of land in a three-dimensional manner. In this model, shading of crops by photovoltaic modules is unavoidable.

[0003] Completely blocking sunlight from photovoltaic modules will result in a loss of photovoltaic power generation, and excessive shading of crops will reduce the duration of sunlight exposure, leading to reduced crop yields. This is especially true for tracking brackets, where higher light energy utilization will result in higher ground shading rates, making the crop yield reduction effect more pronounced.

[0004] How to control the tracking angle of the photovoltaic support to simultaneously ensure photovoltaic power generation and crop sunlight supply is a technical problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0005] In view of the above problems, this application provides a photovoltaic support bracket control method and related device to achieve the goal of simultaneously balancing photovoltaic power generation and crop sunlight supply by controlling the tracking angle of the photovoltaic support bracket. The specific solution is as follows: The first aspect of this application provides a photovoltaic support control method, including: Multiple candidate tracking angles are generated within the physical limits of the tracking bracket; Based on the light saturation and light inhibition characteristics of crops, the ground average irradiance corresponding to each candidate tracking angle is corrected to obtain the effective photosynthetic irradiance corresponding to each candidate tracking angle. Based on the crop shading rate constraint, the segmented electricity price tolerance function, the effective photosynthetic irradiance and the total irradiance of the component surface corresponding to each candidate tracking angle, a hierarchical screening operation is performed on the multiple candidate tracking angles to obtain the target tracking angle. A control command including the target tracking angle is generated to drive the tracking bracket to rotate according to the target tracking angle.

[0006] In one possible implementation, the step of correcting the ground-average irradiance corresponding to each of the candidate tracking angles based on the crop's light saturation and light inhibition characteristics to obtain the effective photosynthetic irradiance corresponding to each of the candidate tracking angles includes: For each candidate tracking angle, calculate the average ground irradiance corresponding to that candidate tracking angle; The ground average irradiance corresponding to each of the candidate tracking angles is converted into photosynthetically active radiation data. Based on the light saturation and light inhibition characteristics of crops, the photosynthetically active radiation data corresponding to each candidate tracking angle are corrected to obtain the effective photosynthetic irradiance corresponding to each candidate tracking angle.

[0007] In one possible implementation, the step of correcting the photosynthetically active radiation data corresponding to each of the candidate tracking angles based on the crop's light saturation and light inhibition characteristics to obtain the effective photosynthetic irradiance corresponding to each of the candidate tracking angles includes: The photosynthetically active radiation data are attenuated based on the canopy absorption parameters to obtain canopy absorbed radiation data; Based on the canopy absorbed radiation data and the preset light saturation threshold, cutoff radiation data is obtained; If the canopy absorbed radiation data is greater than the preset upper limit for light suppression triggering, calculate the light suppression factor; The cutoff radiation data is corrected based on the light suppression factor to obtain the effective photosynthetic irradiance.

[0008] In one possible implementation, based on crop shading rate constraints, a piecewise electricity price tolerance function, the effective photosynthetic irradiance corresponding to each candidate tracking angle, and the total irradiance of the module surface, a hierarchical screening operation is performed on the multiple candidate tracking angles to obtain the target tracking angle, including: Candidate tracking angles that meet the shading rate constraint are selected to obtain the reference tracking angle; Using the effective photosynthetic irradiance corresponding to each of the aforementioned reference tracking angles, an agricultural reference angle is determined from the aforementioned reference tracking angles; Based on the agricultural reference angle, the segmented electricity price tolerance function, and the total surface irradiance of the component corresponding to each reference tracking angle, a filtering operation is performed on the multiple reference tracking angles to obtain the target tracking angle.

[0009] In one possible implementation, candidate tracking angles whose shading rates satisfy the shading rate constraint are selected to obtain reference tracking angles, including: Obtain shading rate constraints; wherein, the process of determining the shading rate constraints includes: determining the current growth stage of the crop based on the crop sowing date and real-time accumulated temperature; if the growth stage is a shading-sensitive period, setting the threshold in the shading rate constraints as a first shading rate threshold; if the growth stage is a non-shading-sensitive period, setting the threshold in the shading rate constraints as a second shading rate threshold; wherein, the first shading rate threshold is less than the second shading rate threshold; Candidate tracking angles with shading rates less than or equal to the threshold in the shading rate constraint are selected to obtain the reference tracking angle.

[0010] In one possible implementation, determining the agricultural reference angle from the reference tracking angles using the effective photosynthetic irradiance corresponding to each of the reference tracking angles includes: Among the reference tracking angles, a set of tracking angles is determined where the effective photosynthetic irradiance is located within a preset effective photosynthetic irradiance range; the preset effective photosynthetic irradiance range is determined based on the maximum effective photosynthetic irradiance. The reference tracking angle with the smallest shading rate in the set of tracking angles is determined as the agricultural reference angle.

[0011] In one possible implementation, the step of filtering the multiple reference tracking angles based on the agricultural reference angle, the segmented electricity price tolerance function, and the total surface irradiance of the component corresponding to each reference tracking angle to obtain the target tracking angle includes: The electricity price tolerance level is determined based on real-time electricity price data and the segmented electricity price tolerance function; The upper limit of the shading rate is determined based on the shading rate corresponding to the agricultural reference angle and the electricity price tolerance. Among the reference tracking angles where the shading rate is less than or equal to the upper limit of the shading rate, the reference tracking angle with the largest total irradiance on the component surface is determined as the target tracking angle.

[0012] A second aspect of this application provides a photovoltaic support control device, comprising: Angle generation module is used to generate multiple candidate tracking angles within the physical limits of the tracking bracket; The correction module is used to correct the ground average irradiance corresponding to each candidate tracking angle based on the light saturation and light inhibition characteristics of the crop, so as to obtain the effective photosynthetic irradiance corresponding to each candidate tracking angle. The screening module is used to perform a hierarchical screening operation on the multiple candidate tracking angles based on the crop shading rate constraint, the segmented electricity price tolerance function, the effective photosynthetic irradiance corresponding to each candidate tracking angle and the total irradiance of the component surface, to obtain the target tracking angle. An angle control module is used to generate control commands including the target tracking angle to drive the tracking bracket to rotate according to the target tracking angle.

[0013] A third aspect of this application provides an electronic device, comprising at least one processor and a memory connected to the processor, wherein: The memory is used to store computer programs; The processor is used to execute the computer program so that the electronic device can implement the photovoltaic support control method described above.

[0014] A fourth aspect of this application provides a computer storage medium carrying one or more computer programs, which, when executed by an electronic device, enable the electronic device to implement the photovoltaic support control method described above.

[0015] By employing the above technical solution, this application provides a photovoltaic support bracket control method and related device. Within the physical limits of the tracking bracket, multiple candidate tracking angles are generated. Based on the light saturation and light inhibition characteristics of the crop, the average ground irradiance corresponding to each candidate tracking angle is corrected to obtain the effective photosynthetic irradiance corresponding to each candidate tracking angle. Based on the crop's shading rate constraint, the piecewise electricity price tolerance function, the effective photosynthetic irradiance corresponding to each candidate tracking angle, and the total irradiance on the module surface, a hierarchical screening operation is performed on the multiple candidate tracking angles to obtain the target tracking angle. A control command including the target tracking angle is generated to drive the tracking bracket to rotate according to the target tracking angle. In other words, this application comprehensively considers the crop's shading situation and irradiance when determining the tracking angle of the tracking bracket, achieving the goal of simultaneously balancing photovoltaic power generation and crop light supply. Attached Figure Description

[0016] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and the originals and elements are not necessarily drawn to scale.

[0017] Figure 1 A flowchart of a photovoltaic support control method provided in this application; Figure 2 A flowchart of a method for determining irradiance provided in this application; Figure 3 A flowchart of a method for determining a target tracking angle provided in this application; Figure 4 This is a structural schematic diagram of a photovoltaic support control device provided in this application; Figure 5 This is a schematic diagram of the structure of an electronic device provided in this application. Detailed Implementation

[0018] The embodiments of this application are described below with reference to the accompanying drawings. The terminology used in the implementation section of this application is for explaining specific embodiments only and is not intended to limit the scope of this application.

[0019] The embodiments of this application will now be described with reference to the accompanying drawings. Those skilled in the art will recognize that, with technological advancements and the emergence of new scenarios, the technical solutions provided in the embodiments of this application are equally applicable to similar technical problems.

[0020] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such terms are interchangeable where appropriate; this is merely a way of distinguishing objects with the same attributes in the embodiments of this application. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion, so that a process, method, system, product, or apparatus that comprises a series of elements is not necessarily limited to those elements but may include other elements not explicitly listed or inherent to those processes, methods, products, or apparatuses.

[0021] Photovoltaic integration is a new land use model that combines photovoltaic power generation with agricultural production on the same piece of land in a three-dimensional manner. In this model, shading of crops by photovoltaic modules is unavoidable.

[0022] Completely blocking sunlight from photovoltaic modules will result in a loss of photovoltaic power generation, and excessive shading of crops will prevent them from receiving sufficient sunlight, leading to reduced crop yields. This is especially true for tracking brackets, where higher light energy utilization leads to higher ground shading rates, resulting in more significant crop yield reductions.

[0023] Currently, in the tracking control of photovoltaic systems that integrate agriculture and solar power, the maximum power generation tracking algorithm can be used to maximize the surface irradiance of the photovoltaic module. The module is always facing the sun, completely ignoring the need for crop protection.

[0024] In addition, a maximum yield tracking algorithm can be used to maximize the effective photosynthetic radiation on the ground, prioritizing crop sunlight but completely ignoring power generation, resulting in low economic returns for the project.

[0025] To simultaneously consider both photovoltaic power generation and crop sunlight supply, a multi-objective optimization method can be adopted. Specifically, a linear weighted combination is used to guarantee both photovoltaic revenue and agricultural revenue, attempting to achieve a trade-off between the two. However, the weighting coefficients lack physical meaning and are difficult to calibrate, and cannot guarantee a minimum yield. Under extreme electricity prices, this may result in excessive sacrifice of crops, thus failing to meet yield requirements.

[0026] To address this, this application provides a photovoltaic support bracket control method and related apparatus. Within the physical limits of the tracking bracket, multiple candidate tracking angles are generated. Based on the crop's light saturation and light inhibition characteristics, the average ground irradiance corresponding to each candidate tracking angle is corrected to obtain the effective photosynthetic irradiance corresponding to each candidate tracking angle. Based on crop shading rate constraints, a piecewise electricity price tolerance function, the effective photosynthetic irradiance corresponding to each candidate tracking angle, and the total irradiance on the module surface, a hierarchical screening operation is performed on the multiple candidate tracking angles to obtain the target tracking angle. A control command including the target tracking angle is generated to drive the tracking bracket to rotate according to the target tracking angle. In other words, this application comprehensively considers the crop's shading situation and irradiance when determining the tracking angle of the tracking bracket, achieving the goal of simultaneously balancing photovoltaic power generation and crop light supply.

[0027] Specifically, the photovoltaic support control method based on light saturation point sensing and segmented electricity price in this application proposes to replace shading rate with effective photosynthetic irradiance as the core indicator for agricultural evaluation. It establishes a four-step effective PAR calculation model of "ground average irradiance (ground PAR (Photosynthetically Active Radiation)) → canopy absorption PAR → light saturation cutoff → light inhibition correction". For the first time, crop physiology (light saturation point, light inhibition trigger threshold, light and midday depression) is directly embedded into the photovoltaic tracking control algorithm, which upgrades agricultural evaluation from physical shading ratio to actual photosynthetic benefits of crops and eliminates physical misjudgments under strong midday light.

[0028] In addition, a "segmented electricity price tolerance function" is proposed to meet the segmented strategy requirements of "low price to protect agriculture, medium price to balance, and high price to promote power generation". A three-segment tolerance function is designed (low price with slow secondary growth, medium price with linear growth, and high price with exponential explosive growth) to make the algorithm behavior accurately match the electricity price range: the tolerance in the low price range approaches 0, and the module locks in the agricultural anchor point; the tolerance in the medium price range grows linearly to achieve both agricultural and solar power; the tolerance in the high price range explodes exponentially, and the module pursues maximum power generation within hard constraints.

[0029] Furthermore, existing technologies employ multi-objective weighted combinations (such as linear weighted summation) and weight coefficients (e.g., photovoltaic weight w_pv=0.6, agricultural weight w_agri=0.4). These weights lack clear physical or economic meaning, making them difficult to scientifically calibrate based on actual project conditions, resulting in poor system versatility. Simultaneously, the weighted method cannot guarantee a yield floor; for example, in extreme scenarios with high electricity prices, the algorithm may excessively sacrifice crop yields in pursuit of profit. This application proposes a three-layer decision-making architecture of "hard constraints + anchor points + tolerance," replacing the traditional weighting method with physically interpretable parameters. It establishes a hierarchical screening architecture: "First layer hard constraints (yield safety red line) → Second layer agricultural anchor points (maximum effective PAR) → Third layer tolerance range (electricity price driven) → Fourth layer maximizing POA." The decision-making process is completely transparent and traceable, with each parameter having a clear physical / physiological / economic meaning (e.g., light saturation point, electricity price benchmark, shading limit). It eliminates the need to rely on "black box" weights and can be directly calibrated based on project conditions (crop variety, electricity price level, yield target).

[0030] In one implementation, refer to Figure 1 A photovoltaic support control method may include: S11. Generate multiple candidate tracking angles within the physical limit range of the tracking bracket.

[0031] Specifically, the physical limit range [-θ_max, θ_max] of the tracking bracket is obtained. The physical limit range is determined by the mechanical structure of the tracking bracket. For example, the physical limit range of a single-axis tracking bracket is usually -60° to +60°.

[0032] Within the physical limits, N candidate tracking angles θ_i (i=1, 2, …, N) are generated with a fixed step size Δθ, where N is a positive integer. The fixed step size Δθ can be set according to the control accuracy requirements and computational efficiency, for example, to 1°, 2°, or 5°.

[0033] S12. Based on the light saturation and light inhibition characteristics of crops, the ground average irradiance corresponding to each candidate tracking angle is corrected to obtain the effective photosynthetic irradiance corresponding to each candidate tracking angle.

[0034] Specifically, for each candidate tracking angle θ_i, the shadow distribution formed by the photovoltaic array at each sampling point on the ground is calculated using a three-dimensional shadow model, and the average ground irradiance I_ground_i is obtained. The three-dimensional shadow model requires DNI (Direct Normal Irradiance) to calculate the geometry of the shadow when calculating the shadow distribution of the photovoltaic array at each sampling point on the ground.

[0035] In real-world scenarios, traditional methods use "ground irradiance" or "shading rate" as agricultural evaluation indicators, assuming that "more sunlight is better for crops." However, crop photosynthesis exhibits a light saturation effect—when sunlight exceeds the light saturation point, excess light cannot be utilized and instead causes photoinhibition damage—photosynthetic efficiency decreases. Therefore, directly using ground irradiance or shading rate as evaluation indicators can incorrectly encourage reduced shading under strong midday sunlight, leading to unnecessary power generation losses. This step introduces the light saturation and photoinhibition characteristics of crops, upgrading agricultural evaluation from "physical shading ratio" to "actual photosynthetic benefit of crops," providing a scientific basis for correct decision-making under strong midday sunlight.

[0036] Specifically, the average ground irradiance is corrected based on the crop's light saturation characteristics (light saturation point) and light inhibition characteristics (light inhibition trigger threshold, light inhibition slope) to obtain the effective photosynthetic irradiance E_i corresponding to each candidate tracking angle θ_i.

[0037] S13. Based on the crop shading rate constraint, the segmented electricity price tolerance function, the effective photosynthetic irradiance and the total irradiance of the component surface corresponding to each candidate tracking angle, a hierarchical screening operation is performed on multiple candidate tracking angles to obtain the target tracking angle.

[0038] Specifically, in this step, a multi-layered screening architecture is adopted, which consists of the following layers: the first layer is absolute hard constraint (shading rate constraint), the second layer is determination of the optimal agricultural anchor point (optimal effective photosynthetic irradiance), the third layer is dynamic tolerance interval (segmented electricity price tolerance function), and the fourth layer is maximization of POA (Plane-of-Array, total irradiance on the component surface). Through layer-by-layer screening, the final target tracking angle is determined from all candidate tracking angles.

[0039] In this step, the design logic of the tiered screening architecture is "narrowing the search layer by layer"—the first layer uses hard constraints to ensure a minimum yield, eliminating all angles that might jeopardize crop yield; the second layer uses effective photosynthetic irradiance to find the best angle for the crop as a benchmark anchor point; the third layer uses electricity price tolerance to expand the search range outward from the benchmark anchor point, with a wider search range as the electricity price increases; the fourth layer selects the tracking angle that generates the most electricity within the searchable range. Each layer's screening criteria have clear physical meaning (shading limit, light saturation point, electricity price benchmark, POA), eliminating the need to rely on weighting coefficients that lack physical meaning. This architecture ensures that the decision-making process is completely transparent and traceable, and that the hard constraint mechanism guarantees that crop yield will not be less than 80% of the yield from undeveloped crops under any circumstances.

[0040] S14. Generate control commands including the target tracking angle to drive the tracking bracket to rotate according to the target tracking angle.

[0041] Specifically, an electronic device, such as a Network Control Unit (NCU), that implements a photovoltaic support control method and related apparatus sends the optimal target tracking angle θ_best to the tracking support controller, such as a Tracker Control Unit (TCU), via a communication network. The TCU generates control commands including the target tracking angle and uses a drive motor to rotate the tracking support to the target tracking angle, thus achieving closed-loop control. The TCU is parallel to the photovoltaic module and has a built-in tilt sensor. The NCU connects to components such as an irradiance sensor, a humidity sensor, and a GPS (Global Positioning System) to collect relevant data.

[0042] In this embodiment, multiple candidate tracking angles are generated within the physical limits of the tracking bracket. Based on the crop's light saturation and light suppression characteristics, the average ground irradiance corresponding to each candidate tracking angle is corrected to obtain the effective photosynthetic irradiance corresponding to each candidate tracking angle. Based on the crop's shading rate constraint, the piecewise electricity price tolerance function, the effective photosynthetic irradiance corresponding to each candidate tracking angle, and the total irradiance on the module surface, a hierarchical screening operation is performed on the multiple candidate tracking angles to obtain the target tracking angle. A control command including the target tracking angle is generated to drive the tracking bracket to rotate according to the target tracking angle. That is, this application comprehensively considers the crop's shading situation and irradiance when determining the tracking angle of the tracking bracket, achieving the goal of simultaneously balancing photovoltaic power generation and crop light supply.

[0043] Based on the above, in one implementation method, refer to Figure 2 Step S12 may include: S21. For each candidate tracking angle, calculate the average ground irradiance corresponding to the candidate tracking angle.

[0044] Specifically, for each candidate tracking angle θ_i, the shadow distribution formed by the photovoltaic array at each sampling point on the ground is calculated using a three-dimensional shadow model, and the average ground irradiance I_ground_i is obtained. Specifically, based on the geometric dimensions of the photovoltaic module, installation height, bracket tilt angle, solar altitude angle, and azimuth angle, it is calculated whether each sampling point is covered by shadow. The irradiance received by uncovered sampling points is GHI (Global Horizontal Irradiance), while the irradiance received by covered sampling points is reduced. Finally, the average irradiance of all sampling points is taken to obtain the average ground irradiance.

[0045] In this step, the 3D shadow model can accurately calculate the shadow distribution at any support angle, offering higher accuracy than the simplified geometric model. The average ground irradiance reflects the average amount of light energy reaching the ground after the photovoltaic modules are shaded, serving as the fundamental input for subsequent calculations of crop photosynthetic yield.

[0046] S22. Convert the average ground irradiance corresponding to each candidate tracking angle into photosynthetically active radiation data.

[0047] In this step, photosynthetically active radiation (PAR) is the only energy source for plants to perform photosynthesis. Of the total solar radiation, only the PAR band is absorbed and utilized by chlorophyll. Converting the average ground irradiance to PAR values ​​eliminates the ultraviolet and infrared bands that crops cannot utilize, making subsequent evaluations more accurate.

[0048] In practice, the ground-average irradiance I_ground_i of the candidate tracking angle θ_i is converted to photosynthetically active radiation PAR_ground_i, with units of μmol / m² / s. The conversion formula is as follows: PAR_ground_i=I_ground_i×α; Wherein, α is the photosynthetically active radiation ratio coefficient, also known as the PAR ratio coefficient, which can be determined based on a large number of experiments.

[0049] S23. Based on the light saturation and light inhibition characteristics of crops, the photosynthetically active radiation data corresponding to each candidate tracking angle are corrected to obtain the effective photosynthetic irradiance corresponding to each candidate tracking angle.

[0050] In this step, after obtaining the photosynthetically active radiation data, a light saturation cutoff operation can be performed on it first, and then the light suppression characteristics can be considered. The light suppression factor is used to perform data calculation operations to obtain the effective photosynthetic irradiance corresponding to each candidate tracking angle.

[0051] In one implementation, step S23 includes: 1) Attenuate the photosynthetically active radiation data based on the canopy absorption parameters to obtain the canopy absorbed radiation data.

[0052] Specifically, not all PAR reaching the top of the crop canopy is utilized by the crop; some is reflected back into the atmosphere by the leaves, while some penetrates the canopy and leaks to the ground. Canopy absorptivity (β) describes the actual PAR interception capacity of the crop canopy, and it varies with crop growth—β is small during the seedling stage when LAI (Leaf Area Index) is low, and large during the vigorous growth stage when LAI is high. Introducing LAI allows the canopy's PAR absorption to reflect changes in the crop's light interception capacity at different growth stages.

[0053] In addition, the extinction coefficient k 消 This reflects the degree to which light is attenuated by leaves as it passes through the canopy, and is related to the growth morphology and spatial distribution angle of the crop leaves—crops with upright leaves (such as corn) allow light to penetrate deeper, resulting in higher attenuation rates (k). 消 The value is relatively small; for crops with flat leaves (such as wheat), a large amount of light energy is intercepted at the top of the canopy, k 消 The value is relatively large. k 消 The value also affects β.

[0054] In this embodiment, LAI and k 消 As parameters for calculating β. Specifically, β is determined by the LAI and k of the current stage. 消 Dynamic calculation, the calculation formula is: β=1-exp(-k 消 ×LAI); LAI reflects the change in crop "leaf volume" as the crop grows, k 消 The characteristics reflecting the "leaf posture" of crop varieties, together with the canopy's ability to absorb and intercept photosynthetically active radiation, are used to determine the overall effectiveness of the canopy in absorbing and capturing photosynthetically active radiation. This is achieved by introducing LAI and k... 消 Dynamic calculations enable the canopy to accurately reflect changes in the light interception capacity of crops at different growth stages by absorbing photosynthetically active radiation.

[0055] β, as the canopy absorption parameter, is used to calculate canopy absorbed radiation data. Specifically, canopy absorbed radiation data refers to canopy absorbed PAR. For a candidate tracking angle θ_i, the canopy absorbed PAR is represented by PAR_absorbed_i, and the calculation formula is: PAR_absorbed_i=PAR_ground_i×β; Where PAR_ground_i represents the photosynthetically active radiation of the candidate tracking angle θ_i.

[0056] In this embodiment, LAI and k are introduced. 消 Dynamic calculations enable canopy absorption PAR to reflect changes in the light interception capacity of crops at different growth stages.

[0057] 2) Based on the canopy absorbed radiation data and the preset light saturation threshold, cutoff radiation data is obtained.

[0058] Specifically, crop photosynthesis exhibits a light saturation effect, meaning that excess light exceeding the light saturation point cannot be utilized. By truncation (taking the minimum of the canopy absorption PAR and the light saturation point), light energy exceeding the LSP (Light Saturation Point) is directly eliminated, effectively avoiding the problem of overestimating crop photosynthetic gains under strong midday sunlight, a problem inherent in traditional methods.

[0059] In specific implementation, the formula for truncating the PAR absorbed by the canopy to the light saturation point LSP is: PAR_sat_i=min(PAR_absorbed_i,LSP); Wherein, PAR_sat_i is the truncated radiation data of the candidate tracking angle θ_i, specifically referring to the photosynthetically active radiation after light saturation truncation, and PAR_absorbed_i is the PAR absorbed by the canopy at the candidate tracking angle θ_i. LSP is the light saturation point of the crop, which is the light intensity when the photosynthetic rate of the crop reaches the maximum. When the light intensity exceeds this value, the photosynthetic rate of the crop no longer increases. The light saturation point varies for different crops, for example, the light saturation point of corn is about 1500 to 1800 μmol / m² / s, and the light saturation point of wheat is about 800 to 1200 μmol / m² / s.

[0060] 3) In the case that the canopy absorbed radiation data is greater than the preset photoinhibition trigger upper limit value, the photoinhibition factor is calculated.

[0061] Specifically, the preset photoinhibition trigger upper limit value can be calculated by "γ×LSP", wherein γ is the photoinhibition trigger threshold, which represents how many times the light intensity exceeds the light saturation point to start triggering photoinhibition.

[0062] When PAR_absorbed_i>γ×LSP, it indicates that there is a risk of photoinhibition judged based on the light intensity before absorption, and the photoinhibition factor is calculated at this time. The calculation formula of the photoinhibition factor is: f_photo_i=1-η×(PAR_absorbed_i / LSP-γ); Wherein, f_photo_i is the photoinhibition factor of the candidate tracking angle θ_i. η is the photoinhibition slope, which represents the severity of photoinhibition; LSP is the light saturation point.

[0063] In actual scenarios, when the light intensity exceeds γ×LSP, the photosynthetic system begins to suffer photoinhibition damage, and the photosynthetic efficiency decreases linearly with the increase of light intensity. The inhibition factor f_photo_i reflects this efficiency loss, and a smaller f_photo_i indicates more severe photoinhibition.

[0064] In this step, strong light can not only fail to increase photosynthesis, but also lead to a decrease in photosynthetic efficiency due to photoinhibition. The present application accurately characterizes this physiological response through the photoinhibition factor correction model. When the light intensity is near the light saturation point (LSP<PAR<γ×LSP), although the crop cannot utilize the excess light energy, it is not significantly damaged; when the light intensity exceeds γ×LSP, the photosynthetic system begins to be damaged and the efficiency decreases. By setting the γ parameter, the trigger threshold of photoinhibition can be precisely controlled, making the model more close to the actual physiological characteristics of different crops.

[0065] 4) Based on the light suppression factor, the cutoff radiation data is corrected to obtain the effective photosynthetic irradiance.

[0066] Specifically, the effective photosynthetic irradiance of the candidate tracking angle θ_i is represented by E_i, which represents the effective light energy actually used by the crop for photosynthesis. It is the core indicator used in this application to evaluate agricultural returns, and its calculation formula is as follows: E_i = PAR_sat_i × f_photo_i; Where E_i is the effective photosynthetic irradiance of the candidate tracking angle θ_i, also known as effective PAR, PAR_sat_i is the cutoff irradiance data of the candidate tracking angle θ_i, and f_photo_i is the light suppression factor of the candidate tracking angle θ_i.

[0067] In this embodiment, the final effective photosynthetic irradiance simultaneously considers three factors: canopy interception capacity, light saturation waste, and light inhibition damage, thus truly reflecting the actual photosynthetic benefits obtained by crops from sunlight. Compared to the shading rate index used in traditional methods, effective photosynthetic irradiance has a clear crop physiological basis and can more accurately guide the tracking and control decisions of photovoltaic supports.

[0068] Based on any of the above embodiments, refer to Figure 3 Step S13 may include: S31. Select candidate tracking angles whose shading rate meets the shading rate constraint to obtain the reference tracking angle.

[0069] In this embodiment, the shading rate constraint is used to filter the tracking angle, which is the first layer of filtering in this application embodiment. The goal of the first layer of filtering is to eliminate all tracking angles with shading rates exceeding the corresponding shading rate threshold in order to ensure the bottom line of crop yield.

[0070] The shading rate constraint includes a shading rate threshold, which can be set differently for different crop growth stages. In one implementation, the process of determining the shading rate constraint includes: 1) Determine the current growth stage of the crop based on the crop sowing date and real-time accumulated temperature.

[0071] Specifically, the current growth stage (Stage_idx) of the crop is determined based on the crop sowing date and the real-time accumulated temperature (GDD, Growing Degree-Days). The growth stage can be seedling stage, maturity stage, flowering stage, grain-filling stage, etc. The real-time accumulated temperature (GDD) can be determined based on the ambient temperature (T_air).

[0072] 2) When the growth stage is a shading-sensitive period, set the threshold in the shading rate constraint to the first shading rate threshold. When the growth stage is not a shading-sensitive period, set the threshold in the shading rate constraint to the second shading rate threshold.

[0073] In real-world scenarios, the first shading rate threshold is less than the second shading rate threshold.

[0074] Specifically, different growth stages have varying degrees of sensitivity to shading—shading during flowering and grain-filling stages directly leads to yield reduction, making them shading-sensitive periods (shading sensitivity coefficient k_shade>0). A stricter first shading rate threshold S_sensitive is used during shading-sensitive periods, setting the threshold in the shading rate constraint to the first shading rate threshold. Shading during seedling and maturity stages has a smaller impact, making them non-shading-sensitive periods (k_shade=0). A relatively lenient second shading rate threshold S_insensitive is used during non-shading-sensitive periods, setting the threshold in the shading rate constraint to the second shading rate threshold. In other words, based on whether the current growth stage is a shading-sensitive period, an absolute shading upper limit is set in the shading rate constraint, i.e., the shading rate threshold S_abs, and the setting principle is as follows: Shading sensitive period (k_shade>0): S_abs=S_sensitive; Non-shade sensitive period (k_shade=0): S_abs=S_insensitive.

[0075] In this step, the crop's response to shading varies greatly at different growth stages—shading during flowering leads to poor pollination and direct yield reduction, while shading during grain filling results in underdeveloped grains. Seedlings and mature plants, however, are more tolerant of shading. Therefore, setting differentiated shading rate thresholds for different growth stages allows for sufficient crop protection during sensitive periods and the appropriate release of shading space for power generation during non-sensitive periods, achieving precise control.

[0076] In practical applications, shading rate constraints can be obtained, and candidate tracking angles with shading rates less than or equal to the threshold in the shading rate constraints can be selected to obtain reference tracking angles.

[0077] The shading rate S_i (range [0,1]) of the candidate tracking angle θ_i is calculated using the following formula: S_i = 1 - I_ground_i / GHI; Where I_ground_i is the ground average irradiance of the candidate tracking angle θ_i, and GHI is the total horizontal irradiance.

[0078] All candidate tracking angles with S_i > S_abs are removed, and only those with S_i ≤ S_abs are retained as reference tracking angles for the next round of selection. Here, S_abs is the shading rate threshold determined based on the current growth stage.

[0079] S32. Using the effective photosynthetic irradiance corresponding to each reference tracking angle, determine the agricultural reference angle from the reference tracking angle.

[0080] The agricultural reference angle refers to the optimal agricultural anchor point, specifically the optimal agricultural angle. Within the reference tracking angles that pass through the first layer of hard constraints, the optimal agricultural anchor point is determined based on effective photosynthetic irradiance.

[0081] In one implementation, step S32 may include: 1) In the reference tracking angle, determine the set of tracking angles where the effective photosynthetic irradiance is located within the preset effective photosynthetic irradiance range.

[0082] The preset effective photosynthetic irradiance range is determined based on the maximum effective photosynthetic irradiance.

[0083] Specifically, the maximum effective photosynthetic irradiance E_max = max(E_i of the reference tracking angle) is determined within the reference tracking angle. A tolerance ε is set to avoid the anchor point jumping between multiple equivalent angles due to numerical noise. Based on the tolerance ε and the maximum effective photosynthetic irradiance, a preset effective photosynthetic irradiance range is determined. The preset effective photosynthetic irradiance range is E_max - ε, meaning it finds the range with the largest effective photosynthetic irradiance.

[0084] Then, the reference tracking angles whose difference between the effective photosynthetic irradiance and E_max is less than or equal to the tolerance ε are used to form the set of tracking angles C={i|E_i of the reference tracking angle ≥ E_max-ε} within the preset effective photosynthetic irradiance range.

[0085] 2) The reference tracking angle with the smallest shading rate in the set of tracking angles is determined as the agricultural reference angle.

[0086] In this step, the second-level screening strategy for anchor point selection employs a two-tiered approach: prioritizing optimal effective PAR and then minimizing shading rate. First, it ensures the crop achieves the best photosynthetic return (maximum effective PAR) under current environmental conditions. Then, within the equivalent photosynthetic return range, it selects the angle most favorable for photovoltaic power generation (minimum shading rate). Furthermore, using effective PAR as an indicator, it correctly identifies the yield equivalence between the two, thereby selecting a horizontal placement angle with higher POA to achieve "no reduction in yield and doubled power generation."

[0087] The introduction of tolerance ε ensures the stability of the anchor points and avoids frequent switching of anchor points due to small numerical fluctuations, thereby ensuring the stability of the support mechanism.

[0088] In this embodiment, the angle with the smallest shading rate is selected from the tracking angle set C as the optimal agricultural anchor point θ_anchor, i.e., the agricultural reference angle. Its calculation formula is as follows: θ_anchor = argmin(reference tracking angle S_i), where i satisfies the reference tracking angle E_i≥E_max-ε.

[0089] Record the shading rate S_anchor = S(θ_anchor) corresponding to the optimal agricultural anchor point.

[0090] S33. Based on the agricultural reference angle, the segmented electricity price tolerance function, and the total irradiance of the component surface corresponding to each reference tracking angle, a screening operation is performed on multiple reference tracking angles to obtain the target tracking angle.

[0091] Specifically, based on real-time electricity prices and segmented electricity price tolerance functions, the searchable shading range is determined starting from the optimal agricultural anchor point in order to determine the target tracking angle.

[0092] In one implementation, step S33 may include: 1) Determine the electricity price tolerance based on real-time electricity price data and the segmented electricity price tolerance function.

[0093] Specifically, the electricity price tolerance is calculated using a piecewise tolerance function based on the real-time electricity price (Price). Electricity price tolerance refers to the magnification factor of the tracking angle of a photovoltaic (PV) bracket relative to the shading rate allowed by the optimal agricultural anchor point under the current real-time electricity price. The piecewise tolerance function is designed in three segments, and each parameter has a clear economic meaning: ; in, As a benchmark for low electricity prices, As the benchmark for China's electricity price, Tolerance for low electricity prices, Tolerance for medium-sized electricity prices, This is the upper limit of tolerance. This is the exponential growth coefficient.

[0094] Specifically, in the formula, the first row of formulas belongs to the tolerance calculation formula for low electricity price areas, the second row of formulas belongs to the tolerance calculation formula for medium electricity price areas, and the third row of formulas belongs to the tolerance calculation formula for high electricity price areas.

[0095] The segmented tolerance function design considers the differences in optimal strategies under different electricity price ranges—in low-price ranges, power generation revenue is low, tolerance is close to 0, and modules are locked to agricultural anchor points to prioritize crop protection; in medium-price ranges, electricity prices are moderate, and tolerance increases linearly to achieve a balance between agriculture and solar power; in high-price ranges, power generation revenue is high, tolerance increases exponentially, and modules freely track the sun within hard constraints. The gradual differences in the three function forms (quadratic slow, linear, and exponential burst) ensure accurate matching between algorithm behavior and electricity price ranges, realizing a segmented strategy of "protecting agriculture at low prices, balancing at medium prices, and prioritizing power generation at high prices."

[0096] When applying the segmented electricity price tolerance function, the real-time electricity price (Price) is substituted into the function to calculate the tolerance level. .

[0097] Electricity price tolerance The calculation formula is: ; Imminent tolerance The minimum value among the tolerance limits is used as the electricity price tolerance level. .

[0098] 2) Determine the upper limit of the shading rate based on the shading rate corresponding to the agricultural reference angle and the electricity price tolerance.

[0099] In this embodiment, the upper limit of the search shading, i.e., the upper limit of the shading rate, is calculated using the following formula: S_limit=min(S_anchor×(1+Tolerance),S_abs); Where S_limit is the upper limit of the shading rate, S_anchor is the shading rate corresponding to the optimal agricultural anchor point, Tolerance is the electricity price tolerance under the current electricity price, and S_abs is the upper limit of the shading rate under the first layer of hard constraints, specifically referring to the shading rate threshold in the shading rate constraint condition. The upper limit of the search shading rate is determined by multiplying the shading rate of the agricultural anchor point by the tolerance factor (1+Tolerance), and is also limited by the absolute hard constraint S_abs. The larger the tolerance, the wider the searchable shading range, but it will not exceed the hard constraint.

[0100] 3) Among the reference tracking angles where the shading rate is less than or equal to the upper limit of the shading rate, the reference tracking angle with the largest total irradiance on the component surface is determined as the target tracking angle.

[0101] Specifically, in the third layer of filtering, reference tracking angles with shading rates S_i ≤ S_limit are selected and added to the candidate set. From the candidate set, the angle with the highest total irradiance on the component surface is chosen as the target tracking angle θ_best, i.e.: θ_best=argmax(P_i), where i satisfies S_i≤S_limit and S_i≤S_abs.

[0102] Where P_i is the POA (Plane of Array, total irradiance on the module surface) of the candidate tracking angle θ_i, and the total irradiance on the photovoltaic module surface is calculated using the inclined plane irradiance conversion model. DHI (Diffuse Horizontal Irradiance) is the basic data for the inclined plane irradiance conversion model.

[0103] The optimal target tracking angle θ_best is then sent to the TCU, which drives the bracket to rotate to the target angle.

[0104] In this step, the fourth layer of screening aims to maximize power generation revenue while satisfying all constraints. Total irradiance (POA) on the module surface represents the actual amount of radiation received by the photovoltaic module for power generation; a higher POA results in higher power generation. By selecting the angle with the highest POA within the feasible area determined by the first three layers, the ultimate goal of "maximizing power generation revenue while protecting crop yields" is achieved. Since the first layer of hard constraints and the second layer of anchor points have ensured the agricultural yield baseline, and the third layer of tolerance has considered electricity price economics, maximizing POA in the fourth layer does not sacrifice agricultural protection.

[0105] In summary, this embodiment has the following advantages: 1. Replace shading rate with effective PAR as an agricultural evaluation indicator to eliminate misjudgment of strong midday sunlight.

[0106] Traditional methods use "shading rate" as an agricultural indicator, assuming that "less shading is better for crops." However, crop photosynthesis has a light saturation effect; under strong midday sunlight, the PAR (particulate energy) of crops placed sideways or horizontally may both exceed the light saturation point, resulting in the same effective photosynthetic benefit. Traditional methods may incorrectly choose sideways placement, leading to power generation loss. This application uses effective PAR as an indicator to correctly identify the yield equivalence between the two methods, thereby selecting a horizontal placement angle with higher POA (particulate energy output) to achieve "no reduction in yield and doubled power generation."

[0107] 2. Introducing light inhibition correction to accurately simulate crop physiological responses.

[0108] This application introduces a light inhibition factor into the effective PAR calculation, where photosynthetic efficiency decreases linearly when light intensity exceeds the light saturation point. This avoids the problem of traditional methods overestimating crop photosynthetic gains under extreme light conditions, making agricultural evaluation more closely reflect actual crop physiology.

[0109] 3. The segmented tolerance function implements a segmented strategy of "protecting farmers with low prices and rushing to sell with high prices".

[0110] Traditional methods employ linear electricity price responses, failing to differentiate between varying policy demands across different price ranges. This application's piecewise tolerance function (low price quadratic slow response, medium price linear response, high price exponential burst response) achieves this: Low-price zones: Tolerance is close to zero; components are locked into agricultural anchors to protect crops. Medium-price zone: Tolerance increases moderately, with a balance between agriculture and solar power; High-price zone: Tolerance index explodes, modules freely follow the sun within hard constraints to maximize power generation revenue.

[0111] 4. Anchor point selection strategy ensures control stability.

[0112] This application selects the angle with the lowest shading rate as the anchor point from among multiple candidates with the highest effective PAR. This avoids the problem of the anchor point jumping between multiple equivalent angles due to numerical noise, ensuring the continuity of control output and the mechanical stability of the support.

[0113] 5. The physical meaning of the parameters is clear and easy to calibrate in engineering.

[0114] All parameters in this application have clear physical / physiological meanings (such as light inhibition threshold, light saturation point, electricity price benchmark, etc.), and can be directly calibrated based on local electricity price levels and crop physiological characteristics without the need for complex machine learning or black-box optimization.

[0115] 6. Absolute hard constraints guarantee the bottom line of production.

[0116] Hard constraints can be set such that the shading rate during the shading-sensitive period does not exceed the first shading rate threshold, and the shading rate during the non-shading-sensitive period does not exceed the second shading rate threshold, to ensure that crop yields are high under any circumstances and meet the basic requirements of agricultural production.

[0117] The above describes a photovoltaic support control method provided by the embodiments of this application. The following will describe the apparatus for performing the photovoltaic support control method described above.

[0118] Please see Figure 4 , Figure 4 This is a schematic diagram of a photovoltaic support control device provided in an embodiment of this application. Figure 4 As shown, the photovoltaic support control device includes: Angle generation module 101 is used to generate multiple candidate tracking angles within the physical limit range of the tracking bracket; The correction module 102 is used to correct the ground average irradiance corresponding to each candidate tracking angle based on the light saturation characteristics and light inhibition characteristics of the crop, so as to obtain the effective photosynthetic irradiance corresponding to each candidate tracking angle. The screening module 103 is used to perform hierarchical screening of multiple candidate tracking angles based on crop shading rate constraints, segmented electricity price tolerance function, effective photosynthetic irradiance corresponding to each candidate tracking angle and total irradiance of component surface, to obtain the target tracking angle. Angle control module 104 is used to generate control commands including the target tracking angle to drive the tracking bracket to rotate according to the target tracking angle.

[0119] In one possible implementation, the correction module 102 includes: The first data calculation submodule is used to calculate the ground average irradiance corresponding to each candidate tracking angle. The second data calculation submodule is used to convert the ground average irradiance corresponding to each candidate tracking angle into photosynthetically active radiation data. The correction submodule is used to correct the photosynthetically active radiation data corresponding to each candidate tracking angle based on the crop's light saturation and light inhibition characteristics, so as to obtain the effective photosynthetic irradiance corresponding to each candidate tracking angle.

[0120] In one possible implementation, the correction submodule includes: The first calculation unit is used to attenuate the photosynthetically active radiation data based on the canopy absorption parameters to obtain the canopy absorbed radiation data. The second calculation unit is used to obtain cutoff radiation data based on canopy absorbed radiation data and a preset light saturation threshold. The third calculation unit is used to calculate the light suppression factor when the canopy absorbed radiation data is greater than the preset light suppression trigger limit. The correction unit is used to correct the cutoff radiation data based on the light suppression factor to obtain the effective photosynthetic irradiance.

[0121] In one possible implementation, the filtering module 103 includes: The first filtering submodule is used to filter out candidate tracking angles whose shading rate meets the shading rate constraint condition, and obtain the reference tracking angle; The angle determination submodule is used to determine the agricultural reference angle from the reference tracking angle using the effective photosynthetic irradiance corresponding to each reference tracking angle; The second filtering submodule is used to filter multiple reference tracking angles based on agricultural reference angles, segmented electricity price tolerance function, and total irradiance of component surface corresponding to each reference tracking angle, to obtain the target tracking angle.

[0122] In one possible implementation, the first filtering submodule includes: The condition acquisition unit is used to acquire shading rate constraints. The process of determining the shading rate constraints includes: determining the current growth stage of the crop based on the crop sowing date and real-time accumulated temperature; when the growth stage is a shading-sensitive period, setting the threshold in the shading rate constraints as a first shading rate threshold; when the growth stage is a non-shading-sensitive period, setting the threshold in the shading rate constraints as a second shading rate threshold; wherein the first shading rate threshold is less than the second shading rate threshold. The filtering unit is used to filter out candidate tracking angles whose shading rate is less than or equal to the threshold in the shading rate constraint, and obtain the reference tracking angle.

[0123] In one possible implementation, the angle determination submodule is specifically used for: In the reference tracking angle, a set of tracking angles is determined where the effective photosynthetic irradiance is within a preset effective photosynthetic irradiance range, and the reference tracking angle with the smallest shading rate in the set of tracking angles is determined as the agricultural reference angle.

[0124] The preset effective photosynthetic irradiance range is determined based on the maximum effective photosynthetic irradiance.

[0125] In one possible implementation, the second filtering submodule includes: The tolerance calculation unit is used to determine the electricity price tolerance based on real-time electricity price data and the segmented electricity price tolerance function; The limit calculation unit is used to determine the upper limit of the shading rate based on the shading rate corresponding to the agricultural reference angle and the electricity price tolerance. An angle determination unit is used to determine the reference tracking angle with the largest total irradiance on the component surface as the target tracking angle among reference tracking angles with a shading rate less than or equal to the upper limit of the shading rate.

[0126] In this embodiment, multiple candidate tracking angles are generated within the physical limits of the tracking bracket. Based on the crop's light saturation and light suppression characteristics, the average ground irradiance corresponding to each candidate tracking angle is corrected to obtain the effective photosynthetic irradiance corresponding to each candidate tracking angle. Based on the crop's shading rate constraint, the piecewise electricity price tolerance function, the effective photosynthetic irradiance corresponding to each candidate tracking angle, and the total irradiance on the module surface, a hierarchical screening operation is performed on the multiple candidate tracking angles to obtain the target tracking angle. A control command including the target tracking angle is generated to drive the tracking bracket to rotate according to the target tracking angle. That is, this application comprehensively considers the crop's shading situation and irradiance when determining the tracking angle of the tracking bracket, achieving the goal of simultaneously balancing photovoltaic power generation and crop light supply.

[0127] It should be noted that the working process of each module, submodule and unit in this embodiment is described in the corresponding description in the above embodiment, and will not be repeated here.

[0128] This application also provides an electronic device, including at least one processor and a memory connected to the processor, wherein: Memory is used to store computer programs; The processor is used to execute computer programs so that the electronic equipment can implement the photovoltaic support control method described above.

[0129] refer to Figure 5 The diagram illustrates a structural schematic suitable for implementing the electronic device in the embodiments of this application. The electronic device in the embodiments of this application may include, but is not limited to, fixed terminals such as mobile phones, laptops, PDAs (personal digital assistants), PADs (tablet computers), desktop computers, NCUs, etc. Figure 5 The electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0130] like Figure 5 As shown, the electronic device may include a processing unit (e.g., a central processing unit, a graphics processing unit, etc.) 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage device 608 into a random access memory (RAM) 603. When the electronic device is powered on, the RAM 603 also stores various programs and data required for the operation of the electronic device. The processing unit 601, ROM 602, and RAM 603 are interconnected via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0131] Typically, the following devices can be connected to I / O interface 605: input devices 606 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 607 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 608 including, for example, memory cards, hard drives, etc.; and communication devices 609. Communication device 609 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 5 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown. More or fewer devices may be implemented or have alternatively.

[0132] This application also provides a computer program product including computer-readable instructions, which, when executed on an electronic device, cause the electronic device to implement any of the photovoltaic bracket control methods provided in this application.

[0133] This application also provides a computer storage medium that carries one or more computer programs. When the one or more computer programs are executed by an electronic device, the electronic device can implement any of the photovoltaic bracket control methods provided in this application.

[0134] It should also be noted that the device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. In addition, in the device embodiment drawings provided in this application, the connection relationship between modules indicates that they have a communication connection, which can be implemented as one or more communication buses or signal lines.

[0135] Through the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware, or it can be implemented by special-purpose hardware including application-specific integrated circuits, special-purpose CPUs, special-purpose memory, special-purpose components, etc. Generally, any function performed by a computer program can be easily implemented by corresponding hardware, and the specific hardware structure used to implement the same function can also be diverse, such as analog circuits, digital circuits, or special-purpose circuits. However, for this application, software program implementation is more often the preferred implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a readable storage medium, such as a computer floppy disk, USB flash drive, mobile hard disk, ROM, RAM, magnetic disk, or optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, training equipment, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0136] In the above embodiments, the implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, in the form of a computer program product.

[0137] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, training device, or data center to another website, computer, training device, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a training device or data center that integrates one or more available media. The available media may be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media (e.g., solid-state drives (SSDs)).

Claims

1. A photovoltaic support control method, characterized in that, include: Multiple candidate tracking angles are generated within the physical limits of the tracking bracket; Based on the light saturation and light inhibition characteristics of crops, the ground average irradiance corresponding to each candidate tracking angle is corrected to obtain the effective photosynthetic irradiance corresponding to each candidate tracking angle. Based on the crop shading rate constraint, the segmented electricity price tolerance function, the effective photosynthetic irradiance and the total irradiance of the component surface corresponding to each candidate tracking angle, a hierarchical screening operation is performed on the multiple candidate tracking angles to obtain the target tracking angle. A control command including the target tracking angle is generated to drive the tracking bracket to rotate according to the target tracking angle.

2. The photovoltaic support control method according to claim 1, characterized in that, The step of correcting the ground-average irradiance corresponding to each candidate tracking angle based on the crop's light saturation and light inhibition characteristics to obtain the effective photosynthetic irradiance corresponding to each candidate tracking angle includes: For each candidate tracking angle, calculate the average ground irradiance corresponding to that candidate tracking angle; The ground average irradiance corresponding to each of the candidate tracking angles is converted into photosynthetically active radiation data. Based on the light saturation and light inhibition characteristics of crops, the photosynthetically active radiation data corresponding to each candidate tracking angle are corrected to obtain the effective photosynthetic irradiance corresponding to each candidate tracking angle.

3. The photovoltaic support control method according to claim 2, characterized in that, The step of correcting the photosynthetically active radiation data corresponding to each candidate tracking angle based on the crop's light saturation and light inhibition characteristics to obtain the effective photosynthetic irradiance corresponding to each candidate tracking angle includes: The photosynthetically active radiation data are attenuated based on the canopy absorption parameters to obtain canopy absorbed radiation data; Based on the canopy absorbed radiation data and the preset light saturation threshold, cutoff radiation data is obtained; If the canopy absorbed radiation data is greater than the preset upper limit for light suppression triggering, calculate the light suppression factor; The cutoff radiation data is corrected based on the light suppression factor to obtain the effective photosynthetic irradiance.

4. The photovoltaic support control method according to claim 1, characterized in that, Based on the crop shading rate constraint, the piecewise electricity price tolerance function, the effective photosynthetic irradiance corresponding to each candidate tracking angle, and the total irradiance of the module surface, a hierarchical screening operation is performed on the multiple candidate tracking angles to obtain the target tracking angle, including: Candidate tracking angles that meet the shading rate constraint are selected to obtain the reference tracking angle; Using the effective photosynthetic irradiance corresponding to each of the aforementioned reference tracking angles, an agricultural reference angle is determined from the aforementioned reference tracking angles; Based on the agricultural reference angle, the segmented electricity price tolerance function, and the total surface irradiance of the component corresponding to each reference tracking angle, a filtering operation is performed on the multiple reference tracking angles to obtain the target tracking angle.

5. The photovoltaic support control method according to claim 4, characterized in that, Candidate tracking angles whose shading rates meet the shading rate constraints are selected to obtain reference tracking angles, including: Obtain shading rate constraints; wherein, the process of determining the shading rate constraints includes: determining the current growth stage of the crop based on the crop sowing date and real-time accumulated temperature; if the growth stage is a shading-sensitive period, setting the threshold in the shading rate constraints as a first shading rate threshold; if the growth stage is a non-shading-sensitive period, setting the threshold in the shading rate constraints as a second shading rate threshold; wherein, the first shading rate threshold is less than the second shading rate threshold; Candidate tracking angles with shading rates less than or equal to the threshold in the shading rate constraint are selected to obtain the reference tracking angle.

6. The photovoltaic support control method according to claim 4, characterized in that, The step of determining the agricultural reference angle from the reference tracking angles using the effective photosynthetic irradiance corresponding to each of the reference tracking angles includes: Among the reference tracking angles, a set of tracking angles is determined where the effective photosynthetic irradiance is located within a preset effective photosynthetic irradiance range; the preset effective photosynthetic irradiance range is determined based on the maximum effective photosynthetic irradiance. The reference tracking angle with the smallest shading rate in the set of tracking angles is determined as the agricultural reference angle.

7. The photovoltaic support control method according to claim 4, characterized in that, The process of filtering the multiple reference tracking angles based on the agricultural reference angle, the segmented electricity price tolerance function, and the total surface irradiance of the component corresponding to each reference tracking angle to obtain the target tracking angle includes: The electricity price tolerance level is determined based on real-time electricity price data and the segmented electricity price tolerance function; The upper limit of the shading rate is determined based on the shading rate corresponding to the agricultural reference angle and the electricity price tolerance. Among the reference tracking angles where the shading rate is less than or equal to the upper limit of the shading rate, the reference tracking angle with the largest total irradiance on the component surface is determined as the target tracking angle.

8. A photovoltaic support control device, characterized in that, include: Angle generation module is used to generate multiple candidate tracking angles within the physical limits of the tracking bracket; The correction module is used to correct the ground average irradiance corresponding to each candidate tracking angle based on the light saturation and light inhibition characteristics of the crop, so as to obtain the effective photosynthetic irradiance corresponding to each candidate tracking angle. The filtering module is used to perform a hierarchical filtering operation on the multiple candidate tracking angles based on the crop shading rate constraint, the segmented electricity price tolerance function, the effective photosynthetic irradiance corresponding to each candidate tracking angle and the total irradiance of the component surface, to obtain the target tracking angle. An angle control module is used to generate control commands including the target tracking angle to drive the tracking bracket to rotate according to the target tracking angle.

9. An electronic device, characterized in that, It includes at least one processor and a memory connected to the processor, wherein: The memory is used to store computer programs; The processor is used to execute the computer program to enable the electronic device to implement the photovoltaic bracket control method as described in any one of claims 1 to 7.

10. A computer storage medium, characterized in that, The computer storage medium carries one or more computer programs, which, when executed by an electronic device, enable the electronic device to implement the photovoltaic support control method as described in any one of claims 1 to 7.

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