Angle control method and device of photovoltaic panel, electronic equipment and storage medium

Abstract

The invention provides an angle control method and device of a photovoltaic panel, electronic equipment and a storage medium, and relates to the technical field of photovoltaic power generation of a power distribution network. The method comprises the steps of obtaining a current inclination angle of a photovoltaic panel, real-time meteorological monitoring data of an area where the photovoltaic panel is located and a sun angle; according to the real-time meteorological monitoring data, determining predicted meteorological monitoring data of the region, the predicted meteorological monitoring data including predicted wind speed, predicted cloud cover and predicted illumination intensity; when the predicted wind speed is greater than a set wind speed threshold value, determining a target inclination angle of the photovoltaic panel according to the current inclination angle of the photovoltaic panel, the wind load corresponding to the predicted wind speed and a wind load threshold value; determining a target azimuth angle of the photovoltaic panel according to the predicted cloud amount, the predicted illumination intensity and the sun angle; and controlling the mechanical adjusting mechanism to adjust the inclination angle of the photovoltaic panel to the target inclination angle and adjust the azimuth angle of the photovoltaic panel to the target azimuth angle. The method is used for achieving the effects of improving the angle control precision and guaranteeing the safety of the photovoltaic panel and the photovoltaic power generation efficiency.

Description

Technical Field

[0001] This application relates to the field of photovoltaic power generation technology in power distribution networks, and in particular to a method, device, electronic equipment and storage medium for controlling the angle of a photovoltaic panel. Background Technology

[0002] Against the backdrop of global energy transition, the development and utilization of renewable energy has become a key strategic measure for countries to achieve sustainable development and address climate change. Solar energy, as an abundant, clean, and widely distributed renewable energy source, has attracted global attention. Photovoltaic power generation, as a major form of solar energy utilization, has achieved large-scale application in the power distribution network sector. As the core component of photovoltaic power plants, photovoltaic panels' power generation efficiency and safe, stable operation are highly dependent on geographical environment and climate conditions. Timely adjustment of the photovoltaic panel angle can better adapt to weather changes and fully realize the power generation potential of photovoltaic power plants. Therefore, controlling the angle of photovoltaic panels is crucial.

[0003] In related technologies, sensors are primarily used to detect environmental parameters in real time. These parameters include at least wind speed, light intensity, temperature, and humidity. Based on these parameters, it is determined whether extreme weather is present. If extreme weather is present, the angle of the photovoltaic panels in the photovoltaic power station is adjusted to a preset fixed angle to adapt to the extreme weather. If no extreme weather is present, astronomical algorithms are used to determine the real-time solar angle, and the angle of the photovoltaic panels is controlled accordingly to ensure that the panels are facing the sun. However, this approach suffers from problems such as low precision in controlling the photovoltaic panel angle, difficulty in ensuring the safety of the photovoltaic panels, and reduced photovoltaic power generation efficiency. Summary of the Invention

[0004] This application provides a method, device, electronic device, and storage medium for controlling the angle of a photovoltaic panel, in order to solve the problems of low angle control accuracy of photovoltaic panels and difficulty in ensuring the safety and photovoltaic power generation efficiency of photovoltaic panels in related technologies.

[0005] In a first aspect, this application provides a method for controlling the angle of a photovoltaic panel, wherein the photovoltaic panel is provided with a mechanical adjustment mechanism, and the angle control method includes:

[0006] Obtain the current tilt angle of the photovoltaic panel, real-time meteorological monitoring data of the area where the photovoltaic panel is located, and the solar angle;

[0007] Based on real-time meteorological monitoring data, predictive meteorological monitoring data for the region is determined. Predictive meteorological monitoring data includes predicted wind speed, predicted cloud cover, and predicted light intensity.

[0008] When the predicted wind speed is greater than the set wind speed threshold, the target tilt angle of the photovoltaic panel is determined based on the current tilt angle of the photovoltaic panel, the wind load corresponding to the predicted wind speed, and the wind load threshold; and the target azimuth angle of the photovoltaic panel is determined based on the predicted cloud cover, predicted light intensity, and solar angle.

[0009] The control mechanism adjusts the tilt angle of the photovoltaic panel to the target tilt angle and the azimuth angle of the photovoltaic panel to the target azimuth angle.

[0010] In one possible implementation, the target tilt angle of the photovoltaic panel is determined based on the current tilt angle of the photovoltaic panel, the wind load corresponding to the predicted wind speed, and the wind load threshold, including:

[0011] If the wind load is greater than or equal to the wind load threshold, then the target tilt angle is determined to be 0.

[0012] If the wind load is less than the wind load threshold, the product of the wind load and the adjustment coefficient is used as the numerator, and the wind load threshold is used as the denominator to obtain the angle to be adjusted; the difference between the current tilt angle and the angle to be adjusted is determined as the target tilt angle, and the adjustment coefficient is used to adjust the magnitude of the tilt angle change.

[0013] In one possible implementation, the solar angle includes the solar azimuth angle and the solar altitude angle. Determining the target azimuth angle of the photovoltaic panel based on predicted cloud cover, predicted solar intensity, and the solar angle includes:

[0014] Based on the predicted cloud cover and predicted light intensity, the solar altitude angle is corrected to obtain the corrected first solar altitude angle.

[0015] Determine the corrected first solar azimuth angle based on the first solar altitude angle;

[0016] The first solar azimuth angle is determined as the target azimuth angle for the photovoltaic panel.

[0017] In one possible implementation, the first solar altitude angle satisfies the following formula:

[0018]

[0019] in, This is the corrected first solar altitude angle; The solar altitude angle before correction; To predict cloud cover; This is the cloud cover correction factor, which characterizes the degree of influence of cloud cover on the correction of the solar altitude angle; This is the light intensity deviation compensation amount, which characterizes the deviation between the predicted light intensity and the theoretical light intensity.

[0020] In one possible implementation, the solar angle includes the solar azimuth angle and the solar altitude angle, and the angle control method further includes:

[0021] When the predicted wind speed is less than or equal to the set wind speed threshold, the target tilt angle of the photovoltaic panel is determined based on the preset calibration table of wind load and tilt angle, according to the wind load corresponding to the predicted wind speed.

[0022] Based on the real-time cloud cover and real-time light intensity contained in the real-time meteorological monitoring data, the solar altitude angle is corrected to obtain the corrected second solar altitude angle;

[0023] Determine the corrected second solar azimuth angle based on the second solar altitude angle;

[0024] The second solar azimuth angle is determined as the target azimuth angle for the photovoltaic panel.

[0025] In one possible implementation, determining the region's predicted meteorological monitoring data based on real-time meteorological monitoring data includes:

[0026] Real-time meteorological monitoring data is input into a pre-trained meteorological data prediction model to obtain the predicted meteorological monitoring data for the region. The meteorological data prediction model is constructed based on a Long Short-Term Memory (LSTM) network.

[0027] In one possible implementation, the angle control method is applied to a cloud server, on which a meteorological data prediction model is deployed.

[0028] Alternatively, the angle control method can be applied to local electronic devices, which are equipped with meteorological data prediction models.

[0029] Secondly, this application provides an angle control device for a photovoltaic panel, wherein a mechanical adjustment mechanism is provided on the photovoltaic panel, and the angle control device includes:

[0030] The acquisition module is used to acquire the current tilt angle of the photovoltaic panel, real-time meteorological monitoring data of the area where the photovoltaic panel is located, and the solar angle.

[0031] The first determining module is used to determine the predicted meteorological monitoring data for the region based on real-time meteorological monitoring data. The predicted meteorological monitoring data includes predicted wind speed, predicted cloud cover, and predicted light intensity.

[0032] The second determining module is used to determine the target tilt angle of the photovoltaic panel based on the current tilt angle of the photovoltaic panel, the wind load corresponding to the predicted wind speed, and the wind load threshold when the predicted wind speed is greater than the set wind speed threshold; and to determine the target azimuth angle of the photovoltaic panel based on the predicted cloud cover, predicted light intensity, and solar angle.

[0033] The control module is used to control the mechanical adjustment mechanism to adjust the tilt angle of the photovoltaic panel to the target tilt angle and the azimuth angle of the photovoltaic panel to the target azimuth angle.

[0034] In one possible implementation, the second determining module is specifically used to: if the wind load is greater than or equal to the wind load threshold, determine the target tilt angle as 0; if the wind load is less than the wind load threshold, use the product of the wind load and the adjustment coefficient as the numerator and the wind load threshold as the denominator to obtain the angle to be adjusted; determine the difference between the current tilt angle and the angle to be adjusted as the target tilt angle, and use the adjustment coefficient to adjust the magnitude of the tilt angle change.

[0035] In one possible implementation, the second determining module is further configured to: correct the solar altitude angle based on the predicted cloud cover and predicted light intensity to obtain a corrected first solar altitude angle; determine the corrected first solar azimuth angle based on the first solar altitude angle; and determine the first solar azimuth angle as the target azimuth angle of the photovoltaic panel.

[0036] In one possible implementation, the first solar altitude angle satisfies the following formula:

[0037]

[0038] in, This is the corrected first solar altitude angle; The solar altitude angle before correction; To predict cloud cover; This is the cloud cover correction factor, which characterizes the degree of influence of cloud cover on the correction of the solar altitude angle; This is the light intensity deviation compensation amount, which characterizes the deviation between the predicted light intensity and the theoretical light intensity.

[0039] In one possible implementation, the solar angle includes the solar azimuth angle and the solar altitude angle. The second determining module is further configured to: when the predicted wind speed is less than or equal to a set wind speed threshold, determine the target tilt angle of the photovoltaic panel based on a preset calibration table of wind load and tilt angle, and according to the wind load corresponding to the predicted wind speed; correct the solar altitude angle according to the real-time cloud cover and real-time light intensity contained in the real-time meteorological monitoring data, to obtain a corrected second solar altitude angle; determine the corrected second solar azimuth angle based on the second solar altitude angle; and determine the second solar azimuth angle as the target azimuth angle of the photovoltaic panel.

[0040] In one possible implementation, the first determining module is specifically used to: input real-time meteorological monitoring data into a pre-trained meteorological data prediction model to obtain predicted meteorological monitoring data for the region, wherein the meteorological data prediction model is constructed based on a long short-term memory network.

[0041] In one possible implementation, the angle control method is applied to a cloud server in which a meteorological data prediction model is deployed; or, the angle control method is applied to a local electronic device in which a meteorological data prediction model is deployed.

[0042] Thirdly, this application provides an electronic device, including: a memory and a processor;

[0043] The memory stores instructions that the computer executes;

[0044] The processor executes computer execution instructions stored in memory, causing the processor to perform the first aspect and / or various possible implementations of the first aspect as described above.

[0045] Fourthly, this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the first aspect and / or various possible embodiments of the first aspect.

[0046] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the first aspect and / or various possible implementations of the first aspect.

[0047] The photovoltaic panel angle control method, device, electronic equipment, and storage medium provided in this application acquire the current tilt angle of the photovoltaic panel, real-time meteorological monitoring data of the area where the photovoltaic panel is located, and the solar angle; based on the real-time meteorological monitoring data, determine the predicted meteorological monitoring data of the area, which includes predicted wind speed, predicted cloud cover, and predicted solar intensity; when the predicted wind speed is greater than a set wind speed threshold, determine the target tilt angle of the photovoltaic panel based on the current tilt angle of the photovoltaic panel, the wind load corresponding to the predicted wind speed, and the wind load threshold; and determine the target azimuth angle of the photovoltaic panel based on the predicted cloud cover, predicted solar intensity, and solar angle; and control the mechanical adjustment mechanism to adjust the tilt angle of the photovoltaic panel to the target tilt angle and the azimuth angle of the photovoltaic panel to the target azimuth angle. In this process, by predicting meteorological monitoring data, changes in meteorological conditions are identified in advance, enabling early prediction of severe weather conditions. When the predicted wind speed exceeds a set wind speed threshold, the tilt angle of the photovoltaic panels is dynamically adjusted in a timely manner based on wind load conditions, improving the wind resistance of the photovoltaic panels to cope with complex and severe weather conditions. This reduces the risk of damage to the photovoltaic panels, achieving a leap from passive response to active protection, and effectively ensuring the safe and stable operation of the photovoltaic panels. The impact of cloud cover and solar intensity on the solar angle is fully considered. By integrating predicted cloud cover, predicted solar intensity, and solar angle, the target azimuth angle of the photovoltaic panels is determined, improving the tracking accuracy of the sun's position, thereby increasing photovoltaic power generation and ensuring power generation efficiency under complex and severe weather conditions. Ultimately, this achieves high-precision, high-safety, and intelligent photovoltaic panel angle control. Attached Figure Description

[0048] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0049] Figure 1 A schematic diagram of a scenario for the photovoltaic panel angle control method provided in an embodiment of this application;

[0050] Figure 2 A flowchart illustrating the angle control method for photovoltaic panels provided in this application embodiment. Figure 1 ;

[0051] Figure 3 A flowchart illustrating the angle control method for photovoltaic panels provided in this application embodiment. Figure 2 ;

[0052] Figure 4 This is a schematic diagram of the structure of the photovoltaic panel angle control device provided in the embodiments of this application;

[0053] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0054] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0055] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0056] The terms “first,” “second,” etc., used in the specification and claims 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 data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented, for example, in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, products, or apparatus.

[0057] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of the relevant data must comply with relevant laws, regulations and standards, and corresponding operation entry points are provided for users to choose to authorize or refuse.

[0058] In related technologies, the main approach is to assess current weather conditions based on real-time collected environmental parameters. Active intervention to improve the wind resistance of photovoltaic (PV) panels is only implemented when weather conditions are severe, adjusting the panel angle to a fixed angle. This passive response method suffers from significant lag, failing to anticipate and implement protective measures before severe weather arrives. This results in substantial safety risks for PV systems during adverse weather conditions, impacting power generation. Furthermore, adjusting the panel angle to a fixed angle fails to consider dynamic wind pressure distribution. Under strong winds, the mechanical structure of the PV panels is prone to excessive localized stress, leading to structural fatigue and shortening the equipment's lifespan. Using astronomical algorithms to determine the real-time solar angle and controlling the PV panel angle accordingly does not consider the influence of meteorological data such as cloud cover and sunlight intensity on the solar angle. This makes it impossible to accurately calculate the sun's true position under complex and variable weather conditions, resulting in inaccurate PV panel angle control and reduced power generation efficiency. Therefore, these technologies suffer from low precision in PV panel angle control, difficulty in ensuring PV panel safety, and compromised PV power generation efficiency.

[0059] The photovoltaic panel angle control method provided in this application, by predicting meteorological conditions in advance, dynamically adjusts the tilt angle of the photovoltaic panel in a timely manner according to wind load when severe weather is detected, thereby improving the wind resistance of the photovoltaic panel and reducing the risk of damage. It also fully considers the impact of cloud cover and sunlight intensity on the solar angle, improving the accuracy of the target azimuth angle of the photovoltaic panel, increasing photovoltaic power generation, and ensuring power generation efficiency under complex and severe meteorological conditions.

[0060] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0061] Figure 1 This is a schematic diagram of a scenario illustrating the photovoltaic panel angle control method provided in the embodiments of this application, such as... Figure 1As shown, the application scenario includes a photovoltaic panel 11 and a computing device 12. The computing device 12 is equipped with an angle control method for the photovoltaic panel. Various types of sensors are deployed on the photovoltaic panel 11, such as light intensity sensors, wind speed sensors, tilt sensors, temperature and humidity sensors, etc. The sensors collect some of the data required by the angle control method. The computing device 12 can obtain the collected data from the sensors. A mechanical adjustment mechanism 13 is installed on the photovoltaic panel 11. The computing device 12 executes the angle control method and controls the operation of the mechanical adjustment mechanism 13 to adjust the angle of the photovoltaic panel 11. Specifically, the mechanical adjustment mechanism 13 includes a transmission mechanism and a gear assembly. It adopts a combination of electric actuator and gear transmission group, which can support bidirectional adjustment of photovoltaic panel 11 in two directions: tilt angle (0°~90°) and azimuth angle (-180°~180°). The electric actuator serves as a power source, and the tilt angle of photovoltaic panel 11 is adjusted by precisely controlling the extension and retraction length of the actuator. The gear transmission group is responsible for adjusting the azimuth angle. Through the meshing transmission of the gears, the photovoltaic panel 11 can rotate in the horizontal direction, thereby accurately aligning with the azimuth of the sun. This mechanical adjustment mechanism has the characteristics of high adjustment accuracy and good stability.

[0062] It should be noted that the computing device 12 is a device with a certain computing power, such as a microcomputer, intelligent controller, embedded system device, server, etc. The computing device 12 can be a local control device, such as one directly installed near the photovoltaic panel or integrated inside the photovoltaic panel; it can also be a centralized control device, such as serving as the control core of a photovoltaic power station, collecting data from each photovoltaic panel and its sensors, and using photovoltaic panel angle control methods to control the angles of different photovoltaic panels within the photovoltaic power station. It should be noted that this application embodiment does not limit the deployment form or number of the computing device 12. Figure 1 This is just one example.

[0063] Figure 2 A flowchart illustrating the angle control method for photovoltaic panels provided in this application embodiment. Figure 1 The execution entity of this angle control method is the computing device 12, such as... Figure 2 As shown, the angle control method includes:

[0064] S201. Obtain the current tilt angle of the photovoltaic panel, real-time meteorological monitoring data of the area where the photovoltaic panel is located, and the solar angle.

[0065] The tilt angle is the angle between the photovoltaic panel and the horizontal ground, ranging from 0° to 90°. When the tilt angle is 0°, the photovoltaic panel is placed horizontally; when the tilt angle is 90°, the photovoltaic panel is perpendicular to the ground. Meteorological monitoring data includes at least wind speed, cloud cover, and solar intensity. Solar angles typically include the solar altitude angle and the solar azimuth angle. The solar azimuth angle is the angle between the sun's projection onto the horizontal plane and the due south direction (Northern Hemisphere) or due north direction (Southern Hemisphere). The solar altitude angle is the angle between the sun's rays and the horizontal plane, ranging from 0° to 90° (maximum at noon, 0° at sunrise and sunset).

[0066] For example, the solar angle can be obtained directly from a meteorological monitoring station, measured by a solar position sensor, or calculated based on astronomical algorithms using the current date, time, and geographical location. Tilt sensors are deployed on the photovoltaic panels to collect their current tilt angle. Real-time meteorological monitoring data can be obtained directly from a meteorological monitoring station, or by installing sensors such as wind speed sensors and light intensity sensors in the area where the photovoltaic panels are located to collect data on light intensity, wind speed, and wind direction. Cloud cover can be measured using a cloud cover observation instrument, or calculated based on the measured and theoretical values ​​from a light intensity sensor. For example, cloud cover can be dynamically calculated using the following formula:

[0067] (1)

[0068] In the formula, Real-time cloud volume; The light intensity is collected in real time by a light intensity sensor; This is the baseline value for light intensity on cloudless days. This value can be pre-determined based on meteorological standards, theoretical model calculations, historical observation statistics, etc.

[0069] S202. Based on real-time meteorological monitoring data, determine the predicted meteorological monitoring data for the region. The predicted meteorological monitoring data includes predicted wind speed, predicted cloud cover, and predicted light intensity.

[0070] Analyzing real-time meteorological monitoring data can yield results that can be used to predict future meteorological data. For example, pre-defined algorithms (such as numerical models) can be used to analyze and process real-time meteorological monitoring data to obtain meteorological data for the region over a future period. Alternatively, artificial intelligence algorithms (such as machine learning or deep learning algorithms) can be used to predict future meteorological data for the region based on current meteorological data.

[0071] S203. When the predicted wind speed is greater than the set wind speed threshold, determine the target tilt angle of the photovoltaic panel based on the current tilt angle of the photovoltaic panel, the wind load corresponding to the predicted wind speed, and the wind load threshold; and determine the target azimuth angle of the photovoltaic panel based on the predicted cloud cover, predicted light intensity, and solar angle.

[0072] The wind speed threshold can be determined by comprehensively considering the structural safety limits of the photovoltaic panel, wind resistance design standards, and meteorological wind speed classification specifications. Wind load is the dynamic pressure exerted by airflow on the surface of the photovoltaic panel. The direction of wind load is perpendicular to the wind direction, and the wind pressure distribution varies significantly depending on the tilt angle of the photovoltaic panel. The wind load distribution is closely related to the tilt angle of the photovoltaic panel. The wind load threshold characterizes the mechanical structural tolerance limit of the photovoltaic panel. For example, the maximum wind pressure value that the photovoltaic panel can withstand is determined by strength testing of the mechanical structure, and the wind load threshold is set based on the maximum wind pressure value.

[0073] The magnitude of wind load is related to wind speed, air density, and the current tilt angle of the photovoltaic panel. For example, wind load can be calculated using the following formula:

[0074] (2)

[0075] In the formula, For wind load; Wind speed; Air density can be obtained through sensors, meteorological monitoring stations, etc. This is the current tilt angle; To standardize the photovoltaic panels at a tilt angle of... The drag coefficient at that time is a dimensionless constant. Calibration can be performed through wind tunnel testing (i.e., calibrating the relationship between tilt angle and drag coefficient). When the tilt angle is 0°, the photovoltaic panel is parallel to the wind direction and the drag coefficient is relatively small. As the tilt angle increases, the drag coefficient will also increase accordingly.

[0076] When the predicted wind speed exceeds a set wind speed threshold, such as 14 m / s, it indicates that extreme (severe) weather conditions (such as strong winds or sandstorms) are imminent, which may cause mechanical damage to the photovoltaic panels. In this case, the angle control of the photovoltaic panels needs to enter wind-resistant mode, triggering the tilt adjustment mechanism in advance. Based on the current tilt angle, wind load, and wind load threshold, the target tilt angle is dynamically determined according to the preset algorithm logic.

[0077] The solar angle obtained in step S201 is the theoretical value under ideal conditions. However, in the actual environment, the solar angle is also affected by meteorological data. Here, cloud cover and light intensity from the meteorological data are combined. For example, based on the solar angle, cloud cover and light intensity, the final solar angle is determined by looking up a table. This table stores the correspondence between solar angle, cloud cover and light intensity. The target azimuth angle of the photovoltaic panel is determined according to the final solar angle.

[0078] S204. The control mechanism adjusts the tilt angle of the photovoltaic panel to the target tilt angle and the azimuth angle of the photovoltaic panel to the target azimuth angle.

[0079] For example, the computing device 12 sends a control command to the mechanical adjustment mechanism. The control command carries at least the photovoltaic panel identifier, the target tilt angle, and the target azimuth angle. The mechanical adjustment mechanism is equipped with a microcontroller to receive the control command and adjust the angle of the photovoltaic panel corresponding to the photovoltaic panel identifier. It should be noted that if the computing device 12 manages multiple distributed photovoltaic panels simultaneously, it sends the corresponding control command to the mechanical adjustment mechanism on each photovoltaic panel separately.

[0080] This application embodiment, by predicting meteorological monitoring data, identifies changes in meteorological conditions in advance, enabling early prediction of severe weather conditions. When the predicted wind speed exceeds a set wind speed threshold, the tilt angle of the photovoltaic panel is dynamically adjusted in a timely manner based on wind load conditions, improving the photovoltaic panel's wind resistance to cope with complex and severe weather conditions. This reduces the risk of photovoltaic panel damage, achieving a leap from passive response to active protection, effectively ensuring the safe and stable operation of the photovoltaic panel. Furthermore, by fully considering the impact of cloud cover and sunlight intensity on the solar angle, the predicted cloud cover, predicted sunlight intensity, and solar angle are integrated to determine the target azimuth angle of the photovoltaic panel. This reduces the interference of environmental factors such as clouds on tracking accuracy, improves the tracking accuracy of the solar position, and increases the efficiency of solar energy reception, thereby increasing photovoltaic power generation and ensuring power generation efficiency under complex and severe weather conditions. Ultimately, this achieves high-precision, high-safety, and intelligent photovoltaic panel angle control.

[0081] In some embodiments, the target tilt angle of the photovoltaic panel is determined based on the current tilt angle of the photovoltaic panel, the wind load corresponding to the predicted wind speed, and the wind load threshold, including:

[0082] Step 1.1: If the wind load is greater than or equal to the wind load threshold, then the target tilt angle is determined to be 0.

[0083] When the wind load at the predicted wind speed is greater than or equal to the wind load threshold, it indicates that the wind load is approaching the withstand limit of the photovoltaic panel structure, posing a serious threat to structural safety. In this case, adjusting the tilt angle of the photovoltaic panel to 0°, making the panel parallel to the wind direction, can minimize wind resistance and protect the structural safety of the photovoltaic panel. hour, , Angle of inclination for the target This represents the maximum wind pressure that the photovoltaic panel can withstand. Indicates the wind load threshold. This is a safety margin constant (considering that in actual situations, there may be sudden changes in wind direction and fluctuations in wind speed, reserving a certain safety redundancy for the structure can ensure that when the wind load is close to but has not yet reached the structural tolerance limit, measures can be taken in advance (adjusting the tilt angle to 0°) to avoid damage to the structure due to instantaneous changes in wind load). The possible value is 0.8.

[0084] Step 1.2: If the wind load is less than the wind load threshold, the product of the wind load and the adjustment coefficient is used as the numerator, and the wind load threshold is used as the denominator to obtain the angle to be adjusted; the difference between the current tilt angle and the angle to be adjusted is determined as the target tilt angle, and the adjustment coefficient is used to adjust the magnitude of the tilt angle change.

[0085] For example, hour, ,in, The adjustment coefficient can be preset according to the actual adjustment performance and mechanical structure characteristics. The algorithm logic dynamically adjusts the tilt angle of the photovoltaic panels based on the magnitude of the wind load, keeping the wind load within the structural safety tolerance range and reducing mechanical losses.

[0086] It should be noted that there is no specific order in which steps 1.1 and 1.2 are executed.

[0087] This application embodiment determines the target tilt angle of the photovoltaic panel by using different angle adjustment rules based on the relationship between wind load and wind load threshold. This diversifies the wind resistance control strategy, ensuring that the photovoltaic panel will not be damaged by excessive wind under normal operating conditions, while also guaranteeing power generation to a certain extent, thus balancing power generation and safety. Compared to related technologies that adjust the photovoltaic panel angle to a fixed angle during severe weather, which cannot dynamically adapt to changes in wind speed, this application embodiment fully considers changes in wind load and dynamically adjusts the tilt angle of the photovoltaic panel to avoid structural fatigue, achieve wind resistance adaptive control, reduce losses and equipment damage risks, thereby reducing maintenance costs and ensuring power generation.

[0088] In some embodiments, the solar angle includes the solar azimuth angle and the solar altitude angle. Determining the target azimuth angle of the photovoltaic panel based on the predicted cloud cover, predicted light intensity, and solar angle includes: correcting the solar altitude angle based on the predicted cloud cover and predicted light intensity to obtain a corrected first solar altitude angle; determining the corrected first solar azimuth angle based on the first solar altitude angle; and determining the first solar azimuth angle as the target azimuth angle of the photovoltaic panel.

[0089] It is understandable that cloud cover and solar radiation intensity are two important environmental factors in the calculation of solar position tracking. When cloud cover increases, the intensity of solar radiation reaching the ground is weakened, and the actual "visible" position of the sun may differ from the theoretically calculated position. The greater the cloud cover, the greater the adjustment range for the solar altitude angle should be, so that the calculated angle can better adapt to the impact of changes in cloud cover. For example, in some embodiments, the corrected first solar altitude angle satisfies the following formula:

[0090] (3)

[0091] in, This is the corrected first solar altitude angle; The solar altitude angle before correction; To predict cloud cover, the value ranges from 0 to 1, where 0 indicates no clouds and 1 indicates complete cloud cover. This is the cloud cover correction factor, which characterizes the degree of influence of cloud cover on the correction of the solar altitude angle, for example, a value of 0.2; This is the light intensity deviation compensation amount, representing the deviation between the predicted and theoretical light intensity. By compensating for the solar altitude angle using this light intensity deviation compensation amount, the first solar altitude angle can more accurately reflect the sun's position under actual lighting conditions, further improving tracking accuracy.

[0092] For example, solar altitude angle Satisfies the following astronomical formula:

[0093] (4)

[0094] In the formula The latitude of the region where the photovoltaic panels are located. The solar declination angle, The solar altitude angle is the hour angle. The solar altitude angle can be obtained using the arcsine function. .

[0095] Sun azimuth Satisfy the following formula:

[0096] (5)

[0097] Will Substituting into the above formula (solar azimuth angle) (In the formula that is satisfied), the corrected first solar azimuth angle can be obtained through the arcsine function. This first solar azimuth angle is taken as the target azimuth angle of the photovoltaic panel.

[0098] In this embodiment, the solar angle is dynamically corrected by comprehensively considering two key environmental factors: cloud cover and light intensity. This reduces the impact of environmental factors on solar tracking accuracy, thereby more accurately determining the sun's position. This helps photovoltaic panels to be more precisely aligned with the sun, improving the utilization efficiency of solar energy and increasing photovoltaic power generation.

[0099] Considering that photovoltaic power generation should be prioritized under normal weather conditions, in some embodiments, the solar angle includes the solar azimuth angle and the solar altitude angle, and the angle control method also includes:

[0100] Step 3.1: When the predicted wind speed is less than or equal to the set wind speed threshold, the target tilt angle of the photovoltaic panel is determined based on the preset calibration table of wind load and tilt angle and the wind load corresponding to the predicted wind speed.

[0101] For example, the wind speed threshold is set to Predicting wind speed This indicates favorable weather conditions, meaning the angle control of the photovoltaic panels does not need to enter wind-resistant mode; at this time, the focus is on increasing power generation.

[0102] In one implementation, the calibration table contains recommended tilt angles for photovoltaic panels under different wind loads. This calibration table, which matches wind load with tilt angle, can be obtained based on wind tunnel test data or actual operating experience to ensure the stability and power generation efficiency of the photovoltaic panels under various wind load conditions. Based on the wind load corresponding to the predicted wind speed, the target tilt angle corresponding to that wind load is found in the calibration table. In practical scenarios, if the wind load value corresponding to the predicted wind speed falls between two values ​​in the calibration table, the closer value can be selected, or interpolation can be used to determine the target tilt angle.

[0103] In another implementation, the calibration table for wind load and tilt angle uses fixed values. These fixed values ​​are typically determined based on a combination of historical experience, experiments, and theoretical research. For example, under favorable weather conditions, the tilt angle corresponding to different wind loads is 45°. This tilt angle usually provides a relatively balanced wind pressure distribution while maintaining a relatively stable receiving area. Based on this, frequent adjustments to the mechanical adjustment mechanism can be reduced, thus lowering mechanical wear.

[0104] Step 3.2: Based on the real-time cloud cover and real-time light intensity contained in the real-time meteorological monitoring data, the solar altitude angle is corrected to obtain the corrected second solar altitude angle; based on the second solar altitude angle, the corrected second solar azimuth angle is determined; the second solar azimuth angle is determined as the target azimuth angle of the photovoltaic panel.

[0105] For example, the real-time cloud cover and real-time light intensity are substituted into the above formula (3) to calculate the second solar altitude angle. The second solar altitude angle is then substituted into the above formula (5), and the corrected second solar azimuth angle can be obtained through the arcsine function. This second solar azimuth angle is then used as the target azimuth angle of the photovoltaic panel.

[0106] Furthermore, in some embodiments, determining the predicted meteorological monitoring data for a region based on real-time meteorological monitoring data includes: inputting the real-time meteorological monitoring data into a pre-trained meteorological data prediction model to obtain the predicted meteorological monitoring data for the region, wherein the meteorological data prediction model is constructed based on a long short-term memory network.

[0107] For example, after obtaining the raw meteorological monitoring data, preprocessing is performed to improve data quality and adapt it to the input requirements of the meteorological data prediction model. Preprocessing operations include, but are not limited to, noise removal, missing value removal, outlier removal, and normalization. After preprocessing, real-time meteorological monitoring data is obtained. This real-time meteorological monitoring data is then input into the meteorological data prediction model. The model extracts and analyzes features from the input data and outputs predicted meteorological monitoring data. The meteorological data prediction model is obtained by iteratively training an LSTM model using meteorological monitoring sample data. LSTM has the ability to process time-series data and can capture long-term dependencies in meteorological data, making it suitable for predicting meteorological parameters. For example, historical meteorological monitoring data such as wind speed, cloud cover, air pressure, and temperature over a historical period are obtained. This meteorological monitoring sample data is used to iteratively optimize the model parameters of the LSTM model. Iteration stops when the model reaches its maximum iteration count or the required model accuracy is achieved.

[0108] In some embodiments, the angle control method is applied to a cloud server in which a meteorological data prediction model is deployed; or, the angle control method is applied to a local electronic device in which a meteorological data prediction model is deployed.

[0109] For example, a cloud server can transmit data with the microcontroller of the mechanical adjustment mechanism on a photovoltaic panel via wireless communication (such as 4G / 5G, Wi-Fi, LoRa, etc.) or wired communication (such as Ethernet). Sensor data from the photovoltaic panel can be reported to the cloud server, which then executes an angle control method to control the operation of the mechanical adjustment mechanism and adjust the angle of the photovoltaic panel. Cloud servers typically possess powerful computing capabilities, enabling them to run complex meteorological data prediction models and improve prediction accuracy. Furthermore, meteorological data prediction models and angle control algorithms can be uniformly updated and maintained in the cloud, reducing the upgrade costs of local equipment. However, wireless communication may experience latency, affecting the real-time performance of angle control, and is highly dependent on the network. If the network connection is unstable or interrupted, the cloud server cannot send commands to the microcontroller of the mechanical adjustment mechanism on the photovoltaic panel, causing angle control failure.

[0110] Another example is the deployment of local electronic devices, such as those directly mounted near or integrated within the photovoltaic panel, which can be directly connected to the microcontroller of the mechanical adjustment mechanism on the panel. This method has low network dependence and strong real-time performance, allowing angle control to continue even in the event of network instability or interruption. However, the computing power and storage space of local electronic devices may be limited, affecting prediction accuracy. Furthermore, updating the meteorological data prediction model or angle control algorithm may require on-site operation, increasing maintenance costs.

[0111] Optionally, on a cloud server, a large-scale dataset is used to iteratively optimize the meteorological data prediction model. The cloud server periodically synchronizes the trained meteorological data prediction model to local electronic devices, and the angle control method is executed on the electronic devices. This balances prediction accuracy and real-time response.

[0112] It should be noted that in actual application deployment, the appropriate deployment method can be selected based on factors such as business needs and geographical environment.

[0113] Figure 3 A flowchart illustrating the angle control method for photovoltaic panels provided in this application embodiment. Figure 2 ,like Figure 3 As shown, the angle control methods include:

[0114] S301. Obtain the current tilt angle of the photovoltaic panel, real-time meteorological monitoring data of the area where the photovoltaic panel is located, and the solar angle.

[0115] For example, the solar angle can be obtained directly from a meteorological monitoring station, measured using a solar position sensor, or calculated based on astronomical algorithms using the current date, time, and geographical location. Tilt sensors are deployed on the photovoltaic panels to collect their current tilt angle. Real-time meteorological monitoring data can be obtained directly from meteorological monitoring stations, or by installing sensors such as wind speed sensors and light intensity sensors in the area where the photovoltaic panels are located to collect data on light intensity, wind speed, and wind direction.

[0116] S302. Input the real-time meteorological monitoring data into the pre-trained meteorological data prediction model to obtain the predicted meteorological monitoring data for the region.

[0117] Among them, the forecast meteorological monitoring data includes forecast wind speed, forecast cloud cover, and forecast light intensity.

[0118] The meteorological data prediction model extracts and analyzes features from the input data and outputs predicted meteorological monitoring data. This model is obtained by iteratively training an LSTM model using meteorological monitoring sample data. LSTM has the ability to process time-series data and can capture long-term dependencies in meteorological data, making it suitable for predicting meteorological parameters.

[0119] S303. Determine whether the predicted wind speed is greater than the set wind speed threshold.

[0120] If the predicted wind speed is greater than the set wind speed threshold, execute S304; if the predicted wind speed is less than or equal to the set wind speed threshold, execute S306.

[0121] S304. Determine the target tilt angle of the photovoltaic panel based on the current tilt angle of the photovoltaic panel, the wind load corresponding to the predicted wind speed, and the wind load threshold.

[0122] Substituting the current tilt angle and predicted wind speed into formula (2), the wind load corresponding to the predicted wind speed is calculated. If the wind load is greater than or equal to the wind load threshold, the target tilt angle is 0; if the wind load is less than the wind load threshold, the target tilt angle is... , The wind load threshold For wind load, For adjustment coefficients, This is the current tilt angle.

[0123] S305. Determine the target azimuth angle of the photovoltaic panel based on the predicted cloud cover, predicted light intensity, and solar angle.

[0124] Substituting the predicted cloud cover, predicted light intensity, and solar angle into formula (3), the corrected first solar altitude angle is calculated. Substituting the first solar altitude angle into formula (5), the corrected first solar azimuth angle can be obtained through the arcsine function. This first solar azimuth angle is used as the target azimuth angle of the photovoltaic panel.

[0125] After determining the target tilt angle and target azimuth angle, proceed to step S308.

[0126] S306. Based on the preset calibration table of wind load and tilt angle, determine the target tilt angle of the photovoltaic panel according to the wind load corresponding to the predicted wind speed.

[0127] The same as step 3.1, so it will not be repeated here.

[0128] S307. Based on the real-time cloud cover and real-time light intensity included in the real-time meteorological monitoring data, the solar altitude angle is corrected to obtain the corrected second solar altitude angle; based on the second solar altitude angle, the corrected second solar azimuth angle is determined; the second solar azimuth angle is determined as the target azimuth angle of the photovoltaic panel.

[0129] The same as step 3.2, so it will not be repeated here.

[0130] S308, The control mechanical adjustment mechanism adjusts the tilt angle of the photovoltaic panel to the target tilt angle and the azimuth angle of the photovoltaic panel to the target azimuth angle.

[0131] For example, a microcontroller is deployed in the mechanical adjustment mechanism to receive control commands and adjust the angle of the photovoltaic panel according to the control commands.

[0132] In summary, this application has at least the following advantages:

[0133] I. By forecasting meteorological monitoring data, changes in meteorological conditions can be identified in advance, enabling early prediction of severe weather conditions. When the predicted wind speed exceeds the set wind speed threshold, the tilt angle of the photovoltaic panels can be dynamically adjusted in a timely manner according to the wind load, thereby improving the wind resistance of the photovoltaic panels to cope with complex and severe weather conditions, reducing the risk of damage to the photovoltaic panels, realizing a leap from passive response to active protection, and effectively ensuring the safe and stable operation of the photovoltaic panels.

[0134] Second, by fully considering the impact of cloud cover and sunlight intensity on the solar angle, and integrating predicted cloud cover, predicted sunlight intensity, and solar angle, the target azimuth angle of the photovoltaic panel is determined. This reduces the interference of environmental factors such as clouds on tracking accuracy, improves the tracking accuracy of the solar position, and increases the solar energy reception efficiency, thereby increasing photovoltaic power generation and ensuring power generation efficiency under complex and severe weather conditions. Ultimately, this achieves high-precision, high-safety, and intelligent photovoltaic panel angle control.

[0135] Third, by leveraging the relationship between wind load and wind load threshold, different angle adjustment rules are used to determine the target tilt angle of the photovoltaic panel, diversifying wind resistance control strategies. This ensures that the photovoltaic panel will not be damaged by excessive wind under normal operating conditions, while also guaranteeing power generation to a certain extent, thus balancing power generation and safety. Compared to related technologies that adjust the photovoltaic panel angle to a fixed angle during severe weather, failing to dynamically adapt to changes in wind speed, this application's embodiment fully considers changes in wind load, dynamically adjusting the photovoltaic panel tilt angle to avoid structural fatigue, achieving wind resistance adaptive control, reducing losses and equipment damage risks, thereby reducing maintenance costs and ensuring power generation.

[0136] Figure 4 This is a schematic diagram of the angle control device for a photovoltaic panel provided in an embodiment of this application. The photovoltaic panel is equipped with a mechanical adjustment mechanism, such as... Figure 4 As shown, the photovoltaic panel angle control device 40 provided in this embodiment includes: an acquisition module 41, a first determination module 42, a second determination module 43, and a control module 44. Wherein:

[0137] The acquisition module 41 is used to acquire the current tilt angle of the photovoltaic panel, real-time meteorological monitoring data of the area where the photovoltaic panel is located, and the solar angle.

[0138] The first determining module 42 is used to determine the predicted meteorological monitoring data of the area based on real-time meteorological monitoring data. The predicted meteorological monitoring data includes predicted wind speed, predicted cloud cover and predicted light intensity.

[0139] The second determining module 43 is used to determine the target tilt angle of the photovoltaic panel based on the current tilt angle of the photovoltaic panel, the wind load corresponding to the predicted wind speed and the wind load threshold when the predicted wind speed is greater than the set wind speed threshold; and to determine the target azimuth angle of the photovoltaic panel based on the predicted cloud cover, the predicted light intensity and the solar angle.

[0140] The control module 44 is used to control the mechanical adjustment mechanism to adjust the tilt angle of the photovoltaic panel to the target tilt angle and the azimuth angle of the photovoltaic panel to the target azimuth angle.

[0141] In one possible implementation, the second determining module 43 is specifically used to: if the wind load is greater than or equal to the wind load threshold, determine the target tilt angle as 0; if the wind load is less than the wind load threshold, use the product of the wind load and the adjustment coefficient as the numerator and the wind load threshold as the denominator to obtain the angle to be adjusted; determine the difference between the current tilt angle and the angle to be adjusted as the target tilt angle, and use the adjustment coefficient to adjust the magnitude of the tilt angle change.

[0142] In one possible implementation, the second determining module 43 is further configured to: correct the solar altitude angle based on the predicted cloud cover and predicted light intensity to obtain a corrected first solar altitude angle; determine the corrected first solar azimuth angle based on the first solar altitude angle; and determine the first solar azimuth angle as the target azimuth angle of the photovoltaic panel.

[0143] In one possible implementation, the first solar altitude angle satisfies the following formula:

[0144]

[0145] in, This is the corrected first solar altitude angle; The solar altitude angle before correction; To predict cloud cover; This is the cloud cover correction factor, which characterizes the degree of influence of cloud cover on the correction of the solar altitude angle; This is the light intensity deviation compensation amount, which characterizes the deviation between the predicted light intensity and the theoretical light intensity.

[0146] In one possible implementation, the solar angle includes the solar azimuth angle and the solar altitude angle. The second determining module 43 is further configured to: when the predicted wind speed is less than or equal to a set wind speed threshold, determine the target tilt angle of the photovoltaic panel based on a preset calibration table of wind load and tilt angle, and according to the wind load corresponding to the predicted wind speed; correct the solar altitude angle according to the real-time cloud cover and real-time light intensity contained in the real-time meteorological monitoring data, and obtain a corrected second solar altitude angle; determine the corrected second solar azimuth angle according to the second solar altitude angle; and determine the second solar azimuth angle as the target azimuth angle of the photovoltaic panel.

[0147] In one possible implementation, the first determining module 42 is specifically used to: input real-time meteorological monitoring data into a pre-trained meteorological data prediction model to obtain predicted meteorological monitoring data for the region, wherein the meteorological data prediction model is constructed based on a long short-term memory network.

[0148] In one possible implementation, the angle control method is applied to a cloud server in which a meteorological data prediction model is deployed; or, the angle control method is applied to a local electronic device in which a meteorological data prediction model is deployed.

[0149] The photovoltaic panel angle control device provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0150] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 5 As shown, the electronic device 50 provided in this embodiment includes at least one processor 501 and a memory 502. Optionally, the electronic device 50 further includes a communication component 503. The processor 501, memory 502, and communication component 503 are connected via a bus 504.

[0151] In a specific implementation, at least one processor 501 executes computer execution instructions stored in memory 502, causing at least one processor 501 to perform the above-described method.

[0152] The specific implementation process of processor 501 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0153] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0154] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0155] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0156] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0157] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method.

[0158] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0159] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0160] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0161] The units described as separate components may or may not be physically separate. 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 units can be selected to achieve the purpose of this embodiment according to actual needs.

[0162] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0163] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0164] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0165] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A method for controlling the angle of a photovoltaic panel, characterized in that, The photovoltaic panel is equipped with a mechanical adjustment mechanism, and the angle control method includes: Obtain the current tilt angle of the photovoltaic panel, real-time meteorological monitoring data of the area where the photovoltaic panel is located, and the solar angle; Based on the real-time meteorological monitoring data, the predicted meteorological monitoring data for the region is determined, and the predicted meteorological monitoring data includes predicted wind speed, predicted cloud cover, and predicted light intensity. When the predicted wind speed is greater than a set wind speed threshold, the target tilt angle of the photovoltaic panel is determined based on the current tilt angle of the photovoltaic panel, the wind load corresponding to the predicted wind speed, and the wind load threshold; and the target azimuth angle of the photovoltaic panel is determined based on the predicted cloud cover, the predicted light intensity, and the solar angle. The mechanical adjustment mechanism is controlled to adjust the tilt angle of the photovoltaic panel to the target tilt angle and the azimuth angle of the photovoltaic panel to the target azimuth angle.

2. The angle control method according to claim 1, characterized in that, Determining the target tilt angle of the photovoltaic panel based on its current tilt angle, the wind load corresponding to the predicted wind speed, and the wind load threshold includes: If the wind load is greater than or equal to the wind load threshold, then the target tilt angle is determined to be 0. If the wind load is less than the wind load threshold, the product of the wind load and the adjustment coefficient is used as the numerator, and the wind load threshold is used as the denominator to obtain the angle to be adjusted; the difference between the current tilt angle and the angle to be adjusted is determined as the target tilt angle, and the adjustment coefficient is used to adjust the magnitude of the tilt angle change.

3. The angle control method according to claim 1, characterized in that, The solar angle includes the solar azimuth angle and the solar altitude angle. Determining the target azimuth angle of the photovoltaic panel based on the predicted cloud cover, the predicted light intensity, and the solar angle includes: Based on the predicted cloud cover and predicted light intensity, the solar altitude angle is corrected to obtain the corrected first solar altitude angle; Based on the first solar altitude angle, determine the corrected first solar azimuth angle; The first solar azimuth angle is determined as the target azimuth angle of the photovoltaic panel.

4. The angle control method according to claim 3, characterized in that, The first solar altitude angle satisfies the following formula: in, This is the corrected first solar altitude angle; The solar altitude angle before correction; To predict cloud cover; This is the cloud cover correction factor, which characterizes the degree of influence of cloud cover on the correction of the solar altitude angle; This is the light intensity deviation compensation amount, which characterizes the deviation between the predicted light intensity and the theoretical light intensity.

5. The angle control method according to any one of claims 1 to 4, characterized in that, The solar angle includes the solar azimuth angle and the solar altitude angle, and the angle control method further includes: When the predicted wind speed is less than or equal to a set wind speed threshold, the target tilt angle of the photovoltaic panel is determined based on a preset calibration table of wind load and tilt angle, according to the wind load corresponding to the predicted wind speed. Based on the real-time cloud cover and real-time light intensity contained in the real-time meteorological monitoring data, the solar altitude angle is corrected to obtain the corrected second solar altitude angle; Based on the second solar altitude angle, determine the corrected second solar azimuth angle; The second solar azimuth angle is determined as the target azimuth angle of the photovoltaic panel.

6. The angle control method according to claim 5, characterized in that, The step of determining the predicted meteorological monitoring data for the region based on the real-time meteorological monitoring data includes: The real-time meteorological monitoring data is input into a pre-trained meteorological data prediction model to obtain the predicted meteorological monitoring data for the region. The meteorological data prediction model is constructed based on a long short-term memory network.

7. The angle control method according to claim 6, characterized in that, The angle control method is applied to a cloud server, where the meteorological data prediction model is deployed. Alternatively, the angle control method may be applied to a local electronic device, in which the meteorological data prediction model is deployed.

8. An angle control device for a photovoltaic panel, characterized in that, The photovoltaic panel is equipped with a mechanical adjustment mechanism, and the angle control device includes: The acquisition module is used to acquire the current tilt angle of the photovoltaic panel, real-time meteorological monitoring data of the area where the photovoltaic panel is located, and the solar angle. The first determining module is used to determine the predicted meteorological monitoring data of the area based on the real-time meteorological monitoring data, wherein the predicted meteorological monitoring data includes predicted wind speed, predicted cloud cover and predicted light intensity. The second determining module is used to determine the target tilt angle of the photovoltaic panel based on the current tilt angle of the photovoltaic panel, the wind load corresponding to the predicted wind speed, and the wind load threshold when the predicted wind speed is greater than a set wind speed threshold; and to determine the target azimuth angle of the photovoltaic panel based on the predicted cloud cover, the predicted light intensity, and the solar angle. The control module is used to control the mechanical adjustment mechanism to adjust the tilt angle of the photovoltaic panel to the target tilt angle and to adjust the azimuth angle of the photovoltaic panel to the target azimuth angle.

9. An electronic device, characterized in that, include: Memory, processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed, are used to implement the method as described in any one of claims 1 to 8.

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