A photovoltaic panel installation optimization method and system based on array cooperation

Abstract

This invention relates to the field of photovoltaic (PV) panel installation technology, specifically disclosing a PV panel installation optimization method and system based on array collaboration. The method includes: controlling the PV array to perform a critical scan to determine the geometric position reference of the PV array; inversely calculating the effective shading margin using the reference and theoretical parameters, and establishing a position deviation profile including malicious deviations; identifying deviation clusters and diffusion boundaries based on the position deviation profile, and formulating an array collaborative gradient correction strategy; mapping the correction strategy to a local correction domain, and constructing an attitude transition buffer for smooth optimization if there is neighboring attitude shearing at the edge. The system includes: a critical scan module, an accuracy analysis module, a gradient optimization module, and a smooth optimization module. This invention is beneficial for achieving quantitative compensation for terrain subsidence and construction errors, and reduces secondary shading through buffers, thereby improving the operational safety of the PV system.

Description

Technical Field

[0001] This invention relates to the field of photovoltaic panel installation technology, and specifically to a photovoltaic panel installation optimization method and system based on array collaboration. Background Technology

[0002] With the large-scale application of photovoltaic power generation technology, adjusting the tilt angle of the modules can reduce the shading of rear-row modules by front-row modules during periods of low solar altitude angle in the early morning and late evening. Traditional inverse tracking algorithms make high assumptions about the constant row spacing of the entire support structure, the uniform pile height, and the absolutely flat ground.

[0003] However, in actual engineering construction and long-term operation and maintenance, due to limitations in construction technology, large-scale piling operations inevitably produce random construction tolerances in row spacing and column height. In addition, photovoltaic power stations are often built in areas with complex geological conditions, and long-term soil subsidence or freeze-thaw cycles can lead to uneven settlement of the foundation. Geometric mismatch can cause the inverse tracking command calculated based on the ideal model to fail: even if the control system considers the current angle to be safe, in the actual physical field, the battery strings of the rear row of modules may still be covered by the shadow of the front row, resulting in hot spot effects and power generation loss.

[0004] Existing technologies typically target point-to-point angle compensation. While this discretized correction, lacking coordination, solves local occlusion problems, it disrupts the overall continuity of the array. Drastic angle differences between rows can cause attitude shearing and may even lead to the corrected high-angle components creating new secondary occlusions on adjacent normal components in the following rows.

[0005] Therefore, the present invention provides a photovoltaic panel installation optimization method and system based on array collaboration. Summary of the Invention

[0006] The purpose of this invention is to provide a photovoltaic panel installation optimization method and system based on array collaboration to solve the aforementioned background problems.

[0007] The objective of this invention can be achieved through the following technical solutions: A photovoltaic panel installation optimization method based on array coordination includes the following steps: The photovoltaic array is controlled to perform critical scanning, and the step time of electrical signals between adjacent components is collected. Based on the step time, the physical alignment point of the shadow edge passing over the battery string is locked. Based on the physical alignment point, the light projection path is deduced to determine the geometric position reference of the photovoltaic array. Theoretical design parameters are obtained and inversely calculated with geometric position references to obtain the effective shading margin between adjacent arrays; the installation accuracy of the photovoltaic array is determined based on the effective shading margin, and a position deviation file is established based on the installation accuracy. Spatial density-based topological analysis is performed on the position deviation archives to identify deviation clusters and diffusion boundaries with malignant deviation states; virtual compensation processing is performed based on the diffusion boundaries to formulate a correction strategy for array cooperative gradient; The gradient correction strategy is mapped to the photovoltaic array cells within the deviation cluster to construct an independent local correction domain; the existence of neighborhood attitude shearing between the edge cells and adjacent cells of the local correction domain is identified; if it exists, an attitude transition buffer is constructed and a smooth optimization strategy is established.

[0008] Furthermore, the method for determining the geometric position reference is as follows: Obtain the direction vector of sunlight; Read the physical dimensions and layout topology of the photovoltaic modules from the parameter manual and installation drawings; Based on physical size parameters and layout topology, and combined with the direction vector of sunlight, a light path projection mapping relationship is established between the top edge of the front row components and the shadowed position of the rear row components. Based on the optical path projection mapping relationship and the physical boundary coordinates of the battery substrings at the receiving end of the rear component, the geometric constraint boundary of the relative position of the front and rear components in three-dimensional space is constructed. Use the geometric constraint boundary as the geometric position reference between arrays under the current lighting conditions.

[0009] Furthermore, the method for obtaining the direction vector of the sunlight is as follows: The latitude and longitude coordinates of the photovoltaic power station and the time information of the physical alignment point are input into a preset astronomical algorithm to calculate the solar altitude angle and solar azimuth angle corresponding to the physical alignment point, and construct the direction vector of sunlight from the center of the sun to the photovoltaic array.

[0010] Furthermore, the method for establishing the aforementioned position deviation file is as follows: By reading the inherent parameters of the photovoltaic module, a physical tolerance boundary is constructed, and the tolerance buffer domain of the photovoltaic module is obtained. Based on the effective shading margin and physical tolerance buffer zone, each photovoltaic array unit is logically graded and marked to establish a position deviation file.

[0011] Furthermore, the effective occlusion margin is obtained as follows: Extract the solar altitude angle corresponding to the physical alignment time point from the geometric position reference, and calculate the relative vertical height difference between the top edge of the front row component and the shadowed battery string of the rear row component; Based on the principle of rectilinear propagation of light and the relationship of triangular projection, the relative vertical height difference is converted into the horizontal projection increment of shadow along the direction of array row spacing by using the solar altitude angle; The difference between the actual physical spacing and the theoretical design spacing between adjacent array rows is defined as the horizontal spacing deviation. Collinear vector superposition analysis is performed on the horizontal projection increment of shadows and the deviation of horizontal spacing to calculate the actual safe distance margin of the shadowed point of the rear row components under the current incident light angle, which is defined as the effective shading margin.

[0012] Furthermore, the virtual compensation process is performed as follows: A virtual compensation surface is constructed based on all photovoltaic array units within the deviation cluster; The nonlinear gradient correction value of each photovoltaic array unit is obtained by performing correction compensation processing based on the virtual compensation surface. Secondary occlusion blocking verification is performed based on nonlinear gradient correction values, and an array-coordinated gradient correction strategy is established.

[0013] Furthermore, the deviation cluster is established as follows: The local maximum search is performed on the photovoltaic array cells by traversing the position deviation file, and the cell with the largest equivalent intrusion depth is determined as the error center cell. Gradient diffusion search is performed starting from the error center unit to establish deviation clusters and diffusion boundaries based on the error gradient.

[0014] Furthermore, the gradient diffusion search is performed as follows: Starting from the error center cell, perform a search to the photovoltaic array cells within the physical neighborhood of the starting point; The ratio of the equivalent intrusion depth of the neighboring cell to the equivalent intrusion depth of the error center cell is defined as the error decay rate. Based on the error decay rate, it is determined whether the neighboring unit and the error center unit belong to the same error distribution domain. If they do, they are included in the current deviation cluster, and the search continues to spread outward from the neighboring unit as a new starting point.

[0015] Furthermore, the method for determining whether neighborhood pose shearing exists is as follows: Traverse the local correction domain and identify photovoltaic array cells that are physically adjacent to the edge correction cells but are not included in the local correction domain, and define them as neighborhood standard cells. The difference between the corrected target angle of the edge correction element and the theoretical design angle of the neighboring standard element is calculated and defined as the attitude shear angle. Establish a comparison logic for neighborhood pose shearing, and obtain a determination result on whether neighborhood pose shearing exists based on the comparison results.

[0016] A photovoltaic panel installation optimization system based on array collaboration includes the following modules: Critical Scan Module: Used to control the photovoltaic array to perform critical scans, collect the step moments of electrical signals between adjacent components, lock the physical alignment point when the shadow edge sweeps across the battery string based on the step moments, and deduce the light projection path based on the physical alignment point to determine the geometric position reference of the photovoltaic array. Accuracy Analysis Module: Used to obtain theoretical design parameters and perform inverse calculations with geometric position benchmarks to obtain the effective shading margin between adjacent arrays; determine the installation accuracy of the photovoltaic array based on the effective shading margin, and establish a position deviation file based on the installation accuracy; Gradient optimization module: used to perform spatial density-based spatial topology analysis on position deviation archives, identify deviation clusters and diffusion boundaries with malignant deviation states; perform virtual compensation processing based on diffusion boundaries, and formulate correction strategies for array cooperative gradients; Smoothing optimization module: used to map gradient correction strategies to photovoltaic array cells within the deviation cluster, construct independent local correction domains; identify whether there is neighborhood attitude shearing between edge cells and adjacent cells of the local correction domain; if so, construct attitude transition buffers and establish smoothing optimization strategies.

[0017] The beneficial effects of this invention are as follows: 1. By controlling the asynchronous differential motion of the front and rear rows of modules and capturing the current step characteristics, the critical state of light path shading, which is difficult to measure directly, is converted into a time signal. The geometric positional relationship between the arrays is analyzed using the rectilinear propagation characteristics of light. The measurement method based on measured photoelectric response helps to reduce the cumulative error introduced by physical factors such as terrain undulation and support deformation in pure visual measurement. The terrain undulation in three-dimensional space is converted into a normalized effective shading margin, and a tolerance buffer domain is established in combination with the physical encapsulation structure of the photovoltaic modules. By distinguishing between benign deviations where shadows fall on non-power generation frame areas and malignant deviations where shadows intrude into the cells, a graded evaluation of the installation accuracy of the photovoltaic array is achieved. The calibration requirements for non-harmful errors are reduced without affecting power generation efficiency, which helps to reduce the amount of subsequent mechanical adjustment work.

[0018] 2. Spatial topology analysis based on spatial density and construction of virtual compensation surfaces are beneficial for identifying the continuous distribution pattern of errors in the array group, transforming discrete single-point fault characteristics into continuous surfaces that reflect the geological subsidence law; using the nonlinear gradient correction strategy generated by the continuous surface, the array's attitude adjustment fits the real terrain undulation trend, which helps to reduce regional systematic occlusion problems, and also improves the consistency of array motion through the continuity characteristics of the surface, further reducing the mechanical stress concentration caused by discrete correction.

[0019] 3. By constructing a local correction domain and monitoring the neighboring attitude shearing state of the edge cells, a transition buffer zone for attitude is established between the correction region and the standard region, and smooth fusion processing is implemented. The gradual transition strategy helps to suppress the spatial topological faults generated at the array boundary due to excessive local angle adjustment, reduce the risk of wind-induced turbulence caused by severe attitude differences, and at the same time reduce the possibility of edge cells causing secondary shading of neighboring standard cells from the geometric optical path, thereby improving the overall safety and stability of photovoltaic power station operation. Attached Figure Description

[0020] The invention will now be further described with reference to the accompanying drawings.

[0021] Figure 1 This is a flowchart of a photovoltaic panel installation optimization method based on array collaboration according to the present invention; Figure 2 This is a flowchart for determining whether neighborhood pose shearing exists in this invention; Figure 3 This is a block diagram of a photovoltaic panel installation optimization system based on array collaboration in this invention. Detailed Implementation

[0022] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below in conjunction with specific embodiments.

[0023] Example 1:

[0024] like Figure 1 As shown, a photovoltaic panel installation optimization method based on array collaboration includes the following steps: S10. Control the photovoltaic array to perform critical scanning, collect the step time of electrical signals between adjacent components, and lock the physical alignment time point when the shadow edge sweeps across the battery string based on the step time point; deduce the light projection path based on the physical alignment time point to determine the geometric position reference of the photovoltaic array. The method for controlling the photovoltaic array to perform critical scanning, acquiring the step moments of electrical signals between adjacent components, and locking the physical alignment point of the shadow edge sweeping across the battery string based on the step moments is as follows: In some embodiments, an active scanning command is sent to the tracking bracket controller of the photovoltaic array to drive the front and rear rows of photovoltaic modules to perform asynchronous differential motion within a preset angle range, thereby creating a dynamic shading process of the front row modules on the rear row modules. For example, the differential motion is performed as follows: the front row photovoltaic modules are controlled to remain at a 45° tilt angle and locked in place, serving as a fixed projection source; at the same time, the rear row photovoltaic modules are driven to continuously rise from the 0° position at a constant speed of 1° per second; through the differential motion of the front row being stationary and the rear row moving, it is beneficial for the rear row photovoltaic modules to actively enter the shadow area projected by the front row photovoltaic modules, thereby achieving a step change in the current under controllable timing. During dynamic shading, the DC current data sequence of the string of photovoltaic modules in the rear row is collected in real time through the high-frequency sampling port of the string inverter; From the DC current data sequence, the drop characteristics of the current amplitude are identified by the sliding difference algorithm, that is, the inflection point timestamp of the current step drop is extracted. The inflection point timestamp is marked as the moment when the shadow edge exactly covers the trigger position of the bypass diode in the battery substring of the rear component, which serves as the physical alignment point; The method for determining the geometric position reference between arrays by inferring the ray projection path based on the physical alignment time point is as follows: Obtain the latitude and longitude coordinates of the photovoltaic power station and the time information of the physical alignment point, and input them into the preset astronomical algorithm for calculation; Preferably, the astronomical algorithm model adopts the SPA algorithm; Based on physical size parameters and layout topology, and combined with the direction vector of sunlight, a light path projection mapping relationship is established between the top edge of the front row components and the shadowed position of the rear row components. Preferably, the method for establishing the optical path projection mapping relationship between the top edge of the front row components and the shadowed position of the rear row components is as follows: Using the upper edge of the front-row components that can produce shadows as the projection source, the spatial projection path of the light is determined by the direction vector of the sunlight. Extend the spatial projection path of the light along the light path direction and calculate the trajectory of the shadow point on the plane where the rear components are located along the straight line. A spatial intersection analysis is performed on the trajectory of the shadow landing point and the physical boundary coordinates of the battery substring at the shadow receiving end of the rear component to construct a geometric constraint boundary describing the relative position of the front and rear components in three-dimensional space. Use the geometric constraint boundary as the geometric position reference between arrays under the current lighting conditions; The geometric position references include: the solar altitude angle corresponding to the physical alignment point; the locked tilt angle of the front row photovoltaic modules and the instantaneous scanning tilt angle of the rear row photovoltaic modules at the physical alignment point, used to characterize the starting and ending points of the measurement; and the relative height of the highest point of the front row modules and the relative height of the shadowed battery strings of the rear row modules, determined based on the module size. It is understandable that the purpose of determining the geometric position reference is: Function 1: Converting time signals into spatial conditions: By capturing the instant of a sudden change in current and utilizing the linearity of sunlight, the true relative distance and relative height difference between the front and rear rows of supports after installation can be determined, which helps to reduce construction errors. Secondly, it serves as a physical anchor point for subsequent optimization: the geometric position benchmark reflects the critical physical state of occlusion, providing a measured and calibrated zero-point reference for subsequent calculations of the unoccluded limit boundary, reducing the theoretical and practical deviations caused by relying solely on design drawings.

[0025] S20. Obtain the theoretical design parameters and perform reverse calculation with the geometric position reference to obtain the effective shading margin between adjacent arrays; determine the installation accuracy of the photovoltaic array based on the effective shading margin, and establish a position deviation file based on the installation accuracy. The method for obtaining the effective occlusion margin between adjacent arrays by acquiring the theoretical design parameters and performing inverse calculations with the geometric position reference is as follows: Extract the solar altitude angle corresponding to the physical alignment time point from the geometric position reference, and calculate the relative vertical height difference between the top edge of the front row component and the shadowed battery string of the rear row component; Based on the principle of rectilinear propagation of light and the relationship of triangular projection, the relative vertical height difference is converted into the horizontal projection increment of shadow along the row spacing direction using the solar altitude angle, so as to characterize the shadow expansion effect caused by terrain subsidence in the horizontal dimension. The difference between the actual physical spacing and the theoretical design spacing between adjacent array rows is defined as the horizontal spacing deviation. Collinear vector superposition analysis was performed on the horizontal projection increment of shadow and the horizontal spacing deviation to calculate the actual safe distance margin of the shadowed point of the rear component under the current incident light angle, which was defined as the effective shading margin after removing the interference of terrain undulation. It should be noted that the method for performing collinear vector superposition analysis on the horizontal projection increment of shadows and the horizontal spacing deviation is as follows: Construct a one-dimensional linear coordinate system along the row spacing direction of the photovoltaic array; The horizontal spacing deviation is defined as a spatial displacement vector. If the actual spacing is greater than the theoretical spacing, the horizontal spacing deviation is assigned a positive attribute (indicating an expansion of the safe space), and vice versa. The horizontal projection increment of the shadow is defined as the light path intrusion vector. Based on the shadow's coverage of the gap, the light path intrusion vector is given a negative attribute (indicating that the safe space is occupied). Within the one-dimensional linear coordinate system, an algebraic summation operation is performed on the spatial displacement vector and the optical path intrusion vector. The result of the operation is the effective occlusion margin under the current illumination conditions after eliminating the interference of three-dimensional terrain undulations. The method for determining the installation accuracy of the photovoltaic array based on the effective shading margin, and for establishing a position deviation file based on the installation accuracy, is as follows: S201. Read the inherent parameters of the photovoltaic module to construct the physical tolerance boundary and obtain the tolerance buffer domain of the photovoltaic module; The preferred method for constructing physical fault tolerance boundaries is as follows: Read the inherent parameters from the photovoltaic module's packaging specifications, including: the width of the bottom frame of the photovoltaic module and the width of the insulation gap from the bottom edge of the lowest cell to the inside of the frame; The width of the bottom border is summed with the width of the insulation gap, and combined with a preset safety factor, to construct a physical tolerance buffer zone that can accommodate shadows without causing power loss. It should be noted that the safety margin coefficient ranges from 1.1 to 1.3, preferably 1.2; the basic physical clearance is multiplied by the safety margin coefficient, and the result is used as the width threshold of the physical tolerance buffer zone, thereby constructing a fault-tolerant boundary that can accommodate dynamic disturbances without causing power loss. S202. Based on the effective shading margin and physical tolerance buffer zone, each photovoltaic array unit traversed is logically graded and marked to establish a position deviation file. Preferably, the logical hierarchical marking process is as follows: If the effective shading margin of the photovoltaic array unit is positive, it indicates that the projection endpoint of the front row shadow has not touched the physical lower edge of the rear row components, and the photovoltaic array unit is determined to be in an absolutely safe state and marked as requiring no processing; If the effective shading margin is negative, but the absolute value is less than the width of the physical tolerance buffer zone, it indicates that although the shadow covers the solid part of the rear module, the landing area is limited to the non-power generation frame or insulation layer, and the main body of the cell is not shaded. The photovoltaic array unit is judged to be in a benign deviation state and marked as a no-work zone. If the effective shading margin is negative and its absolute value exceeds the width of the physical tolerance buffer zone, it indicates that the shadow has substantially invaded the power generation area of ​​the solar cell, and the photovoltaic array unit is judged to be in a state of malignant deviation. If the state is determined to be a malignant deviation, the portion of the shadow intrusion length that exceeds the physical tolerance buffer zone is calculated and defined as the equivalent intrusion depth. The photovoltaic modules throughout the field are examined, and only the number of the photovoltaic array unit in a state of severe deviation and its corresponding equivalent intrusion depth are stored in the position deviation file, while photovoltaic array units in an absolutely safe state and a benign deviation state are filtered out. It should be noted that a photovoltaic array unit refers to the smallest mechanical tracking subsystem equipped with an independent drive motor (such as a single-row independent tracking bracket); the deviation data in the position deviation file is mapped one-to-one with the control ID of the drive motor.

[0026] Example 2:

[0027] Please see Figure 1As shown, a photovoltaic panel installation optimization method based on array collaboration includes the following steps: S30. Perform spatial density-based spatial topology analysis on the position deviation archive to identify deviation clusters and diffusion boundaries with malignant deviation states; perform virtual compensation processing based on the diffusion boundaries to formulate a correction strategy for array cooperative gradient; The method for identifying deviation clusters and diffusion boundaries with malignant deviation states by performing spatial topological analysis based on spatial density on the position deviation archive is as follows: S301. Traverse the position deviation file to perform a local maximum search on the photovoltaic array unit and determine the unit with the largest equivalent intrusion depth as the error center unit. S302. Starting from the error center unit, perform gradient diffusion search to establish deviation clusters and diffusion boundaries based on the error gradient; The preferred method for performing gradient diffusion search is as follows: Starting from the error center cell, perform a search to the photovoltaic array cells within the physical neighborhood of the starting point; The ratio of the equivalent intrusion depth of the neighboring cell to the equivalent intrusion depth of the error center cell is defined as the error decay rate. The error decay rate is compared with a preset correlation threshold. If it is higher than the threshold, the neighboring unit and the error center unit are determined to belong to the same error distribution domain. The neighboring unit is included in the current deviation cluster, and the search continues to spread outward from the neighboring unit as a new starting point. It should be noted that the correlation threshold ranges from 0.6 to 0.8 (preferably 0.7). If the error decay rate is higher than this threshold, it indicates that the neighboring unit and the error center unit have a strong geological correlation in terms of physical settlement and belong to the continuous extension of the same settlement structure, so it is included in the current deviation cluster; if the error decay rate is lower than this threshold, it indicates that the error of the neighboring unit has undergone a cliff-like decay, belonging to random construction error or the edge of another independent settlement area, and does not have topological continuity, so it is not included in the current deviation cluster. If the error decay rate of the neighboring unit is lower than the correlation threshold, or if a photovoltaic array unit in an absolutely safe state is encountered, the search in the corresponding direction is stopped, and the search termination position is marked as the diffusion boundary of the current deviation cluster. The method for formulating the array cooperative gradient correction strategy based on virtual compensation processing of the diffusion boundary is as follows: S311. Construct a virtual compensation surface based on all photovoltaic array units within the deviation cluster: Preferably, the method for constructing the virtual compensation surface is as follows: Extract the physical coordinates and corresponding equivalent intrusion depths of all photovoltaic array units within the deviation cluster, and construct a three-dimensional deviation discrete point set; A spatial interpolation algorithm is used to generate a virtual compensation surface that can cover all malicious deviation state units and whose curvature changes continuously based on a three-dimensional deviation discrete point set; It should be noted that the spatial interpolation algorithm is a radial basis function algorithm using a Gaussian kernel function, and the virtual compensation surface is represented as the minimum terrain fitting shape required to eliminate all terrain subsidence effects in the region. The physical meaning of the virtual compensation surface is to replace the fragmented and discrete individual errors with a smooth and continuous surface. S312. Based on the virtual compensation surface, perform correction compensation processing to obtain the nonlinear gradient correction value of each photovoltaic array unit; Preferably, the correction and compensation process is performed by calculating the normal vector of the tangent plane of the virtual compensation surface at each coordinate point of the photovoltaic array unit. The angle between the normal vector of the tangent plane and the normal vector of the theoretical ground plane is analyzed to obtain the nonlinear gradient correction value for each photovoltaic array unit; S313. Perform secondary occlusion blocking verification based on nonlinear gradient correction values ​​and establish an array-coordinated gradient correction strategy: Preferably, the method for performing secondary shading blocking verification and establishing an array-coordinated gradient correction strategy is to preload the nonlinear gradient correction value into the corresponding photovoltaic array unit. And perform shading risk comparison processing, that is, whether the photovoltaic array unit after applying the correction value will cause new projection shading to the photovoltaic array unit behind it due to the excessive increase in angle, which is defined as secondary shading risk; If a secondary shading risk is detected, the correction magnitude of the photovoltaic array unit is reduced, and the reduction magnitude is proportionally distributed to the photovoltaic array units adjacent to it in front, thus eliminating the secondary shading risk through a multi-level sharing method. The nonlinear gradient correction value that passes the verification is confirmed as the array-coordinated gradient correction strategy and then issued for execution.

[0028] S40. Map the correction strategy to the photovoltaic array units within the deviation cluster to construct an independent local correction domain; identify whether there is neighborhood attitude shearing between the edge units and adjacent units of the local correction domain; if so, construct an attitude transition buffer and establish a smooth optimization strategy. The method for mapping the gradient correction strategy to the photovoltaic array cells within the deviation cluster and constructing an independent local correction domain is as follows: Extract the nonlinear gradient correction value generated by S30 and send it to the corresponding photovoltaic array unit controller within the deviation cluster; The set of photovoltaic array cells that accept nonlinear gradient correction values ​​is defined as the local correction domain, and the photovoltaic array cells located at the outermost boundary of the local correction domain are marked as edge correction cells; The method for identifying whether there is neighborhood pose shearing between edge cells and adjacent cells in the local correction domain is as follows: Traverse the local correction domain and identify photovoltaic array cells that are physically adjacent to the edge correction cells but are not included in the local correction domain, and define them as neighborhood standard cells. Simulate the critical moment of the inverse tracking phase, calculate the difference between the corrected target angle of the edge correction unit and the theoretical design angle of the neighboring standard unit, and define it as the attitude shear angle; like Figure 2 As shown, a shear tolerance threshold is set (e.g.) Preferred If the absolute value of the attitude shear angle is less than the shear tolerance threshold, it is determined that there is no neighboring attitude shear, and local correction is allowed to be performed directly. If the absolute value of the attitude shear angle is greater than or equal to the shear tolerance threshold, it is determined that there is a neighboring attitude shear, indicating that there is a spatial topological fault between the local correction domain and the external standard region, and smoothing processing between the photovoltaic arrays needs to be triggered. Preferably, the method for triggering smoothing is as follows: Using the edge correction unit as the boundary, extend outwards a preset number of neighboring standard units (e.g., 1-3 rows), redefining the photovoltaic array units within the extended range as a transition buffer zone for attitude. A cosine smooth interpolation algorithm is used to calculate the transition correction value for each photovoltaic array unit within the attitude transition buffer to ensure the continuity of the angle change rate. For example, the transition correction value is calculated as follows: Get transition correction value ; in: Here, d represents the nonlinear gradient correction value of the edge correction unit, and d is the row distance from the current unit to the edge correction unit. , The total number of rows set for the transition buffer; It should be noted that the transition correction value formula is in The correction amount is ,exist The correction is zero at the point and the derivatives at both ends are zero, achieving a smooth C1 continuous transition from the correction domain to the standard domain, which is beneficial for suppressing wind-induced turbulence and mechanical shear stress. The transition correction value is superimposed on the base angle command of each unit in the attitude transition buffer, so that the array attitude gradually decreases from the high correction amount in the local correction domain through the buffer and finally smoothly merges into the zero correction state of the external standard region, thus achieving smooth processing. It should be noted that the purpose of constructing the pose transition buffer and performing weighted smooth fusion processing is: Function 1: Reduce the risk of wind-induced turbulence: If there is a sudden change in the angle of a local area (such as a difference of 10° between two adjacent rows), strong wind shear and turbulence will be generated in the gap between the arrays, increasing the risk of microcracks in the components; a smooth transition can maintain the aerodynamic characteristics of the overall streamlined shape of the array; Function 2: Reduce secondary projection shading: Severe angular shearing often reflects a sharp difference in physical height, which can easily cause the edge correction unit to shade the external standard unit at dawn and dusk. By establishing a buffer zone, it is beneficial to reduce the probability of secondary shading hazards in photovoltaic modules.

[0029] Example 3:

[0030] Please see Figure 3 As shown, a photovoltaic panel installation optimization system based on array collaboration includes the following modules: Critical Scan Module: Used to control the photovoltaic array to perform critical scans, collect the step moments of electrical signals between adjacent components, lock the physical alignment point when the shadow edge sweeps across the battery string based on the step moments, and deduce the light projection path based on the physical alignment point to determine the geometric position reference of the photovoltaic array. Accuracy Analysis Module: Used to obtain theoretical design parameters and perform inverse calculations with geometric position benchmarks to obtain the effective shading margin between adjacent arrays; determine the installation accuracy of the photovoltaic array based on the effective shading margin, and establish a position deviation file based on the installation accuracy; Gradient optimization module: used to perform spatial density-based spatial topology analysis on position deviation archives, identify deviation clusters and diffusion boundaries with malignant deviation states; perform virtual compensation processing based on diffusion boundaries, and formulate correction strategies for array cooperative gradients; Smoothing optimization module: used to map gradient correction strategies to photovoltaic array cells within the deviation cluster, construct independent local correction domains; identify whether there is neighborhood attitude shearing between edge cells and adjacent cells of the local correction domain; if so, construct attitude transition buffers and establish smoothing optimization strategies.

[0031] The foregoing has provided a detailed description of one embodiment of the present invention, but this description is merely a preferred embodiment and should not be construed as limiting the scope of the invention. All equivalent variations and modifications made within the scope of the present invention should still fall within the scope of the present invention.

Claims

1. A photovoltaic panel installation optimization method based on array coordination, characterized in that, Includes the following steps: The photovoltaic array is controlled to perform critical scanning, and the step time of electrical signals between adjacent components is collected. Based on the step time, the physical alignment point of the shadow edge passing over the battery string is locked. Based on the physical alignment point, the light projection path is deduced to determine the geometric position reference of the photovoltaic array. The theoretical design parameters are obtained and inversely calculated with the geometric position reference to obtain the effective occlusion margin between adjacent arrays; The installation accuracy of the photovoltaic array is determined based on the effective shading margin, and a position deviation file is established based on the installation accuracy. Spatial density-based topological analysis is performed on the position deviation archives to identify deviation clusters and diffusion boundaries with malignant deviation states; virtual compensation processing is performed based on the diffusion boundaries to formulate a correction strategy for array cooperative gradient; The gradient correction strategy is mapped to the photovoltaic array cells within the deviation cluster to construct an independent local correction domain; the existence of neighborhood attitude shearing between the edge cells and adjacent cells of the local correction domain is identified; if it exists, an attitude transition buffer is constructed and a smooth optimization strategy is established.

2. The photovoltaic panel installation optimization method based on array collaboration according to claim 1, characterized in that: The method for determining the geometric position reference is as follows: Obtain the direction vector of sunlight; Read the physical dimensions and layout topology of the photovoltaic modules from the parameter manual and installation drawings; Based on physical size parameters and layout topology, and combined with the direction vector of sunlight, a light path projection mapping relationship is established between the top edge of the front row components and the shadowed position of the rear row components. Based on the optical path projection mapping relationship and the physical boundary coordinates of the battery substrings at the receiving end of the rear component, the geometric constraint boundary of the relative position of the front and rear components in three-dimensional space is constructed. Use the geometric constraint boundary as the geometric position reference between arrays under the current lighting conditions.

3. The photovoltaic panel installation optimization method based on array collaboration according to claim 2, characterized in that: The method for obtaining the direction vector of the sunlight is as follows: The latitude and longitude coordinates of the photovoltaic power station and the time information of the physical alignment point are input into a preset astronomical algorithm to calculate the solar altitude angle and solar azimuth angle corresponding to the physical alignment point, and construct the direction vector of sunlight from the center of the sun to the photovoltaic array.

4. The photovoltaic panel installation optimization method based on array collaboration according to claim 1, characterized in that: The method for establishing the aforementioned position deviation file is as follows: By reading the inherent parameters of the photovoltaic module, a physical tolerance boundary is constructed, and the tolerance buffer domain of the photovoltaic module is obtained. Based on the effective shading margin and physical tolerance buffer zone, each photovoltaic array unit is logically graded and marked to establish a position deviation file.

5. The photovoltaic panel installation optimization method based on array collaboration according to claim 4, characterized in that: The effective occlusion margin is obtained as follows: Extract the solar altitude angle corresponding to the physical alignment time point from the geometric position reference, and calculate the relative vertical height difference between the top edge of the front row component and the shadowed battery string of the rear row component; Based on the principle of rectilinear propagation of light and the relationship of triangular projection, the relative vertical height difference is converted into the horizontal projection increment of shadow along the direction of array row spacing by using the solar altitude angle; The difference between the actual physical spacing and the theoretical design spacing between adjacent array rows is defined as the horizontal spacing deviation. Collinear vector superposition analysis is performed on the horizontal projection increment of shadows and the deviation of horizontal spacing to calculate the actual safe distance margin of the shadowed point of the rear row components under the current incident light angle, which is defined as the effective shading margin.

6. The photovoltaic panel installation optimization method based on array collaboration according to claim 1, characterized in that: The virtual compensation process is performed as follows: A virtual compensation surface is constructed based on all photovoltaic array units within the deviation cluster; The nonlinear gradient correction value of each photovoltaic array unit is obtained by performing correction compensation processing based on the virtual compensation surface. Secondary occlusion blocking verification is performed based on nonlinear gradient correction values, and an array-coordinated gradient correction strategy is established.

7. The photovoltaic panel installation optimization method based on array collaboration according to claim 6, characterized in that: The deviation cluster is established as follows: The local maximum search is performed on the photovoltaic array cells by traversing the position deviation file, and the cell with the largest equivalent intrusion depth is determined as the error center cell. Gradient diffusion search is performed starting from the error center unit to establish deviation clusters and diffusion boundaries based on the error gradient.

8. The photovoltaic panel installation optimization method based on array collaboration according to claim 7, characterized in that: The gradient diffusion search is performed as follows: Starting from the error center cell, perform a search to the photovoltaic array cells within the physical neighborhood of the starting point; The ratio of the equivalent intrusion depth of the neighboring cell to the equivalent intrusion depth of the error center cell is defined as the error decay rate. Based on the error decay rate, it is determined whether the neighboring unit and the error center unit belong to the same error distribution domain. If they do, they are included in the current deviation cluster, and the search continues to spread outward from the neighboring unit as a new starting point.

9. The photovoltaic panel installation optimization method based on array collaboration according to claim 1, characterized in that: The method for determining whether neighborhood pose shearing exists is as follows: Traverse the local correction domain and identify photovoltaic array cells that are physically adjacent to the edge correction cells but are not included in the local correction domain, and define them as neighborhood standard cells. The difference between the corrected target angle of the edge correction element and the theoretical design angle of the neighboring standard element is calculated and defined as the attitude shear angle. Establish a comparison logic for neighborhood pose shearing, and obtain a determination result on whether neighborhood pose shearing exists based on the comparison results.

10. A photovoltaic panel installation optimization system based on array collaboration, used to implement the photovoltaic panel installation optimization method based on array collaboration as described in any one of claims 1-9, characterized in that, Includes the following modules: Critical Scan Module: Used to control the photovoltaic array to perform critical scans, collect the step moments of electrical signals between adjacent components, lock the physical alignment point when the shadow edge sweeps across the battery string based on the step moments, and deduce the light projection path based on the physical alignment point to determine the geometric position reference of the photovoltaic array. Accuracy analysis module: used to obtain theoretical design parameters and perform inverse calculations with geometric position references to obtain the effective occlusion margin between adjacent arrays; The installation accuracy of the photovoltaic array is determined based on the effective shading margin, and a position deviation file is established based on the installation accuracy. Gradient optimization module: used to perform spatial density-based spatial topology analysis on position deviation archives, identify deviation clusters and diffusion boundaries with malignant deviation states; perform virtual compensation processing based on diffusion boundaries, and formulate correction strategies for array cooperative gradients; Smoothing optimization module: used to map gradient correction strategies to photovoltaic array cells within the deviation cluster, construct independent local correction domains; identify whether there is neighborhood attitude shearing between edge cells and adjacent cells in the local correction domain; if so, construct attitude transition buffers and establish smoothing optimization strategies.

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