Intelligent light following control method and system for photovoltaic support, medium and program product

Abstract

The invention provides an intelligent light following control method and system for a photovoltaic support, a medium and a program product, and relates to the technical field of intelligent control. The method comprises the following steps: acquiring local geography and current time information, and acquiring current illumination intensity through a plurality of light sensors; and when the illumination intensity exceeds the preset starting threshold value, controlling a plurality of image acquisition devices on the photovoltaic panel to shoot a shadow of a measuring marker post located at the center of the photovoltaic panel, and obtaining image data. And then, geography, time and shadow image data are input into a shadow benchmark analysis model, and the model is trained and constructed through a deep learning algorithm based on a local solar azimuth change rule, an actually measured benchmark shadow and optimal power generation angle data of the photovoltaic panel, so that photovoltaic panel adjustment parameters are determined. And finally, a control instruction is sent to the motor according to the parameters, so that the photovoltaic panel automatically faces the sun. By implementing the method, the motor can be driven to enable the photovoltaic panel to accurately follow light, and solar energy is fully utilized, so that the power generation efficiency is improved.

Description

Technical Field

[0001] The present application relates to the field of intelligent control technology, and in particular to a method, system, medium and program product for intelligent light tracking control of a photovoltaic bracket. Background Art

[0002] With the development of social economy, the demand for clean and renewable energy is increasing. As one of the clean and renewable energy sources, solar energy has attracted extensive attention due to its low power generation cost and abundant resources. Photovoltaic power generation, as one of the important ways to utilize solar energy, converts sunlight into electrical energy through photovoltaic panels and has been widely used in various scenarios. In order to improve the power generation efficiency of photovoltaic power generation systems, it is necessary to enable photovoltaic panels to face the moving sun in real time to ensure that the photovoltaic panels are always directly exposed to sunlight.

[0003] Currently, some photovoltaic sun-tracking systems use mechanical or electronic photosensors to measure the direction of sunlight and drive the photovoltaic panels to rotate to the corresponding angle. This method calculates the approximate direction of sunlight based on the light intensity information collected by the light sensor.

[0004] However, the traditional method still cannot accurately reflect the specific position of the sun through light intensity information, and thus cannot meet the higher requirements for tracking accuracy. Summary of the invention

[0005] The present application provides a method, system, medium and program product for intelligent light-chasing control of a photovoltaic bracket, which are used to accurately determine the specific position of the sun and adjust the photovoltaic panels accordingly to achieve intelligent light-chasing control.

[0006] In the first aspect, the present application provides an intelligent light-chasing control method for a photovoltaic bracket, which is applied to a light-chasing control system, the method comprising: obtaining local geographic information and current time information; obtaining current light intensity through multiple light sensors; if the light intensity exceeds a preset start threshold, controlling multiple image acquisition devices on the photovoltaic panel to capture the shadow of a measuring benchmark to obtain shadow image data, wherein the measuring benchmark is placed at the center of the photovoltaic panel; inputting the geographic information, the current time information and the shadow image data into a shadow benchmark analysis model to determine photovoltaic panel adjustment parameters, wherein the shadow benchmark analysis model is constructed in advance based on the local sun's azimuth angle change law in different seasons and different time periods, and combined with multiple measured benchmark shadow data and corresponding preset photovoltaic panel optimal power generation angle data using a deep learning algorithm for training; sending a control instruction to the motor corresponding to the photovoltaic bracket according to the photovoltaic panel adjustment parameters to make the photovoltaic panel automatically face the sun.

[0007] By adopting the above technical solution, the local geographic information and current time are first accurately obtained, which provides a basic spatiotemporal background for subsequent light chasing. The light sensor monitors the light intensity in real time. Once the threshold is exceeded, the measurement benchmark at the center of the photovoltaic panel cooperates with the image acquisition equipment to capture the shadow image. These data inputs are based on the local solar laws, the measured benchmark shadow and the shadow benchmark analysis model trained with the optimal power generation angle data. The adjustment parameters of the photovoltaic panel can be accurately calculated, and the driving motor allows the photovoltaic panel to accurately chase the light, making full use of solar energy and greatly improving the power generation efficiency.

[0008] In combination with some embodiments of the first aspect, in some embodiments, before the step of sending a control instruction to the motor according to the photovoltaic panel adjustment parameters to make the photovoltaic panel face the sun, it also includes: constructing a photovoltaic panel historical adjustment data set to record in real time the adjustment parameters of the photovoltaic panel in a certain period of time in the past; analyzing the photovoltaic panel historical adjustment data set to generate a photovoltaic panel adjustment range model; inputting the target time period into the photovoltaic panel adjustment range model to obtain a reasonable range of variation of the photovoltaic panel adjustment parameters; judging whether the photovoltaic panel adjustment parameters exceed the reasonable range of variation; if they exceed the reasonable range of variation, redetermining the photovoltaic panel adjustment parameters to make the photovoltaic panel adjustment parameters within the reasonable range of variation.

[0009] By adopting the above technical solution and using historical experience to set limits on adjustment parameters, we can prevent errors or abnormal parameters from misleading adjustments, ensure stable operation of photovoltaic panels, avoid invalid adjustments that cause loss of power generation efficiency, and make the light-chasing system more reliable and generate electricity continuously and efficiently.

[0010] In combination with some embodiments of the first aspect, in some embodiments, if the reasonable variation range is exceeded, the photovoltaic panel adjustment parameters are redetermined to make the photovoltaic panel adjustment parameters within the reasonable variation range. The step also includes: after obtaining the current power generation data of the photovoltaic panel in real time, the current power generation data and the photovoltaic panel adjustment parameters are input into a pre-set photovoltaic power generation prediction model to predict the adjusted power generation prediction value, and the photovoltaic power generation prediction model is trained in advance based on multiple historical photovoltaic panel adjustment parameter combinations and corresponding actual power generation data in different seasons, different weather conditions, and different time periods; the power generation prediction value is compared with the actual power generation before adjustment to calculate the power generation increase value; if the power generation increase value is lower than the preset minimum increase value, it is determined that the current light chasing control strategy is not effective, and the photovoltaic panel adjustment parameters are redetermined again.

[0011] By adopting the above technical solution, the predicted power generation value is compared with the actual value to calculate the improvement value, and the advantages and disadvantages of the chasing strategy are judged accordingly. Inefficient strategies can be detected in time, and the parameters can be optimized and adjusted again to dynamically adapt to changes in light, ensuring that the power generation efficiency is steadily improved and maintaining the efficient output of the photovoltaic system.

[0012] In combination with some embodiments of the first aspect, in some embodiments, before the step of obtaining the current light intensity through multiple light sensors, it also includes: obtaining real-time power data of the battery in the photovoltaic system; pre-establishing a lookup table of the correspondence between the battery power and the number of light chasing times; querying the lookup table to obtain the number of light chasing times corresponding to the real-time power data; if the time interval between two light chasing controls is less than the preset minimum time interval, modifying the number of light chasing times to make the time interval between the two light chasing controls greater than or equal to the preset minimum time interval; determining the light chasing time and light chasing frequency based on the modified number of light chasing times.

[0013] By adopting the above technical solution, the battery power is taken into consideration to control the chasing of light, and the battery power is prevented from being depleted due to frequent chasing of light when the power is low. Sufficient power is guaranteed to support chasing of light and power generation, balance the energy consumption of the two, improve the comprehensive utilization efficiency of energy, and make the photovoltaic system operate stably.

[0014] In combination with some embodiments of the first aspect, in some embodiments, before the step of sending a control instruction to the motor corresponding to the photovoltaic bracket according to the adjustment parameters of the photovoltaic panel to make the photovoltaic panel automatically face the sun, it also includes: obtaining wind speed data and wind direction data through a wind speed sensor; if the wind speed data is greater than a preset wind speed threshold, or the wind direction data is opposite to the light chasing direction, it is determined that the current environment is not suitable for light chasing, and the current light chasing control is paused to keep the position of the photovoltaic panel unchanged.

[0015] By adopting the above technical solution, before sending instructions to the motor, the wind speed sensor is used to monitor the wind speed and wind direction. When the wind speed exceeds the standard or the wind is against the standard, the solar chasing is suspended to maintain the position of the photovoltaic panel. This avoids the damage to the equipment caused by strong wind and headwind, and avoids the energy consumption of chasing against the wind. It not only protects the equipment to extend its life and reduce the operation and maintenance costs, but also ensures the chasing of solar energy under suitable weather conditions, stably obtains solar energy, and guarantees the efficiency of power generation.

[0016] In combination with some embodiments of the first aspect, in some embodiments, after the step of sending a control instruction to the motor corresponding to the photovoltaic bracket according to the photovoltaic panel adjustment parameters to make the photovoltaic panel face the sun, it also includes: real-time monitoring of the photovoltaic bracket status through the image acquisition device; after receiving the bracket status viewing instruction sent by the user end, sending the photovoltaic bracket status to the user end for display; receiving the photovoltaic panel adjustment instruction sent by the user end, adjusting the photovoltaic panel according to the photovoltaic panel adjustment instruction.

[0017] By adopting the above technical solutions, on the one hand, the bracket can be monitored in real time to prevent failures and ensure operation; on the other hand, the user's desire for remote control can be met, and the photovoltaic panels can be flexibly adjusted to cope with special or daily working conditions, thereby improving user experience, enhancing system practicality, and ensuring power generation continuity.

[0018] In combination with some embodiments of the first aspect, in some embodiments, if the light intensity exceeds a preset start threshold, then after the step of controlling multiple image acquisition devices on the photovoltaic panel to capture the shadow of the measuring benchmark to obtain shadow image data, it also includes: if the shadow length of the measuring benchmark in the shadow image data is less than the set length, it is determined that the current position of the photovoltaic panel meets the requirements of power generation efficiency, the position of the photovoltaic panel is kept unchanged and the shadow benchmark analysis model is not used for light chasing control.

[0019] By adopting the above technical solution, simple shadow length judgment can be used to avoid unnecessary model calculations and motor actions, save computing resources and energy consumption, maintain efficient power generation, and improve system stability and power generation efficiency.

[0020] In a second aspect, the present application provides a server, comprising: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to cause the server to execute the method described in the first aspect and any possible implementation of the first aspect.

[0021] In a third aspect, the present application provides a computer-readable storage medium comprising instructions, which, when executed on a server, causes the server to execute the method described in the first aspect and any possible implementation of the first aspect.

[0022] In a fourth aspect, the present application provides a computer program product, which, when executed on a server, enables the server to execute the method described in the first aspect and any possible implementation manner of the first aspect.

[0023] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. The technical means of using local geographic and time information, combined with light intensity threshold triggering, using a central measuring pole and image acquisition to obtain shadow images and inputting a shadow pole analysis model based on local solar laws to drive the motor to adjust the photovoltaic panels has effectively solved the technical problems of poor light tracking accuracy and inability to fully utilize solar energy in the existing technology, thereby achieving the technical effect of accurate light tracking and greatly improving power generation efficiency.

[0024] 2. Due to the technical means of constructing a historical adjustment data set of photovoltaic panels to generate adjustment range model verification parameters, and combining real-time power generation data with a prediction model based on multi-historical condition training to judge the pros and cons of the chasing strategy and secondary optimize the parameters, the technical problems of photovoltaic panel adjustment parameters being easy to get out of control and chasing strategies being difficult to optimize in the existing technology are effectively solved, thereby achieving the technical effect of dynamically adapting to light, steadily improving power generation efficiency, and ensuring efficient output of photovoltaic systems.

[0025] 3. The technology of using a wind speed sensor to monitor wind speed and direction before sending instructions to the motor and suspending light chasing according to the threshold and wind direction conditions is adopted. Therefore, the technical problems of photovoltaic equipment being easily damaged by bad weather and energy consumption in headwind light chasing in the prior art are effectively solved, thereby achieving the technical effect of protecting equipment, reducing operation and maintenance costs, stably obtaining solar energy, and ensuring power generation efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 This is a flow chart of the intelligent light tracking control method for a photovoltaic bracket in an embodiment of the present application; Figure 2 This is another flow chart of the intelligent light tracking control method for a photovoltaic bracket in an embodiment of the present application; Figure 3 It is a schematic diagram of the structure of a physical device of a light chasing control system in an embodiment of the present application. DETAILED DESCRIPTION

[0027] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification and appended claims of the present application, the singular expressions "one", "a kind of", "said", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to and includes any or all possible combinations of one or more listed items.

[0028] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more.

[0029] For ease of understanding, the following is a description of the process of the method provided by this implementation. Figure 1 , which is a flow chart of the intelligent light tracking control method for a photovoltaic bracket in an embodiment of the present application.

[0030] S101, obtaining local geographic information and current time information; In the light-chasing control system, obtaining local geographic information and current time information is the cornerstone of achieving accurate light-chasing. Geographic information covers key elements such as longitude and latitude, altitude, etc. Longitude and latitude determine the basic movement trajectory of the sun in the sky. Different latitude positions make the change patterns of the sun's altitude angle and azimuth angle significantly different. It is also crucial to obtain current time information. The position of the sun continues to change throughout the day, and its azimuth and altitude angles change measurably every minute. Accurate time information combined with geographic information can calculate the theoretical position of the sun relative to the local area at the current moment through astronomical algorithms. In actual operation, the light-chasing control system can obtain accurate geographic information by connecting to the global positioning system (GPS) module. GPS satellites can provide high-precision longitude and latitude data. The time information can be obtained by the built-in real-time clock (RTC). The RTC can maintain accurate time counting after the system is powered off, ensuring that the system can quickly obtain the correct time after restarting.

[0031] S102, obtaining current light intensity through multiple light sensors; Multiple light sensors are reasonably distributed around the photovoltaic panels and the surrounding environment to form a monitoring network. These light sensors can sense the light intensity in different directions and positions. Its working principle is based on the photoelectric effect. When light shines on the photosensitive element of the sensor, it causes the electrical characteristics of the photosensitive element to change, thereby generating an electrical signal related to the light intensity. Through the collaborative work of multiple light sensors, the distribution of the light field can be fully understood. In actual scenes, there may be complex situations such as partial occlusion, light reflection or scattering. If there is only a single light sensor, it is likely to misjudge the overall lighting conditions due to partial occlusion. Multiple light sensors can comprehensively analyze the light data at different locations and accurately determine whether there is occlusion and the true level of light intensity.

[0032] In some embodiments, before this step, the system will first obtain the real-time power data of the battery in the photovoltaic system. The acquisition of this data is usually achieved through a sensor connected to the battery management system. The sensor can accurately measure the current power of the battery and convert it into a digital signal to transmit to the light chasing control system. In order to reasonably regulate the consumption of battery power by the light chasing operation, the system pre-establishes a lookup table of the corresponding relationship between the battery power and the number of light chasing. The construction of this lookup table is based on a comprehensive analysis of the photovoltaic system and a large amount of experimental data. Under different battery power levels, the system has determined the appropriate number of light chasing after testing to ensure that the battery has enough power to support the light chasing operation and maintain other basic functions of the entire photovoltaic system. After obtaining the real-time power data, the system will quickly query the above-mentioned lookup table to determine the number of light chasing corresponding to the power data. Next, the system will check whether the time interval between two light chasing controls is less than the preset minimum time interval. The current time interval between the two light chasing controls is less than the preset minimum time interval, indicating that the light chasing operation is too frequent and may cause a risk of over-discharge of the battery. In this case, the system will automatically modify the number of light chasing to the number of times that the time interval between the two light chasing controls is greater than or equal to the preset minimum time interval. For example, if the original plan is to chase the light four times per hour, but the current time interval will cause the battery to over-discharge, the system may adjust the number of chasing lights to three times per hour or less, depending on the battery power, time interval, and the system's optimization algorithm. Finally, based on the modified number of chasing lights, the system will re-determine the chasing time and frequency. For example, if the modified number of chasing lights is three times per hour, the system will evenly distribute these three chasing light operations at different time points within an hour, ensuring that while ensuring power generation efficiency, the battery life is protected to the maximum extent, the stable operation of the photovoltaic system is maintained, and efficient energy utilization and sustainable operation of the system are achieved.

[0033] S103, if the light intensity exceeds a preset start threshold, controlling multiple image acquisition devices on the photovoltaic panel to capture the shadow of a measuring pole placed at the center of the photovoltaic panel to obtain shadow image data; In the light chasing control system, when the light intensity exceeds the preset start threshold, the image acquisition process is triggered. First of all, the setting of the preset start threshold is obtained through a large number of experiments and data analysis. Taking into account the differences in lighting conditions in different regions, the performance characteristics of photovoltaic panels, and the energy consumption and operating costs of the system, a threshold is selected that can ensure that the system is started when there is enough light for effective light chasing, but will not be too sensitive and start frequently, resulting in equipment loss and energy waste. For example, in sunny desert areas, the threshold may be relatively high because the light intensity is generally strong; in some mountainous areas with changeable climates and relatively weak light, the threshold will be appropriately lowered, but it should also be avoided that it is too low and the system is frequently mistakenly started on cloudy days or during low light periods.

[0034] The measuring pole is placed at the center of the photovoltaic panel. The height of the pole should be moderate. If it is too high, it may cause large shaking or resistance in bad weather such as strong winds, affecting the stability of the shadow and the accuracy of image acquisition, and may even damage the photovoltaic panel. If it is too low, it may not be able to produce a sufficiently long and clear shadow when the solar altitude angle is large, which is not conducive to subsequent analysis. Usually, according to the size of the photovoltaic panel and the common local solar altitude angle range, the height of the pole is determined through simulation and actual testing. The measuring pole is used to produce a shadow when illuminated by the sun to facilitate the tracking control system to determine the specific position of the sun.

[0035] Multiple image acquisition devices on the photovoltaic panel, such as high-definition cameras, are installed according to a specific layout. The field of view of these cameras needs to cover the measuring pole and its surrounding area to ensure that the shadow of the pole can be fully captured. The installation angle enables it to obtain the best shooting angle under different sun positions and lighting conditions. The resolution of the camera should be high enough, generally not less than 1080p, to clearly distinguish the details of the shadow, including the edge contour of the shadow, the scale mark of the length measurement (which can be set in advance), etc. At the same time, the camera also has automatic adjustment functions, such as autofocus, automatic adjustment of exposure time and white balance. In the case of sudden changes in light intensity or light conditions at different times, the autofocus function can ensure that the shadow always remains clear; the automatic adjustment of exposure time can avoid overexposure of the image due to excessive light or blurring of the shadow due to too dark light; white balance adjustment ensures the authenticity of the image color and prevents the judgment of the shadow from being affected by changes in light color temperature. When the light intensity exceeds the threshold, the control system quickly sends instructions to these image acquisition devices to start the shooting program. After receiving the instructions, the device starts to collect images at the same time and transmits the collected image data to the control system in real time.

[0036] In some embodiments, after completing the image acquisition of the shadow of the measuring pole, the system will conduct an in-depth analysis of the shadow image data. If the shadow length of the measuring pole in the shadow image data is less than the set length, it is determined that the current position of the photovoltaic panel meets the requirements of power generation efficiency, and the position of the photovoltaic panel remains unchanged. Among them, the determination of the set length is based on a large number of preliminary experiments and data analysis, and is combined with the physical characteristics and power generation principles of the photovoltaic panel. Under different lighting conditions, seasonal changes and geographical locations, the length of the pole shadow corresponding to the optimal power generation angle of the photovoltaic panel will be different. Through tests in a variety of environmental scenarios, researchers have calculated the approximate range of the length of the pole shadow under the condition of meeting efficient power generation. At the same time, in order to further save system resources, the system will suspend the use of the shadow pole analysis model for subsequent calculations and light tracking control processes. Because in this case, it is no longer practical to perform complex model calculations and parameter adjustments, which will only increase the burden on the system. Through this intelligent judgment mechanism, the system can achieve optimal resource allocation under the premise of ensuring power generation efficiency, improve the stability and economy of the entire photovoltaic system, and ensure the efficient and sustainable operation of the photovoltaic power generation process.

[0037] S104, inputting the geographic information, the current time information and the shadow image data into a shadow benchmark analysis model to determine the photovoltaic panel adjustment parameters, wherein the shadow benchmark analysis model is constructed by using a deep learning algorithm training in advance according to the local sun's azimuth angle variation law in different seasons and different time periods, and in combination with a plurality of measured benchmark shadow data and corresponding preset photovoltaic panel optimal power generation angle data; The shadow benchmark analysis model is a key model used to determine the adjustment parameters of photovoltaic panels based on the input geographic information, time information and shadow image data. The construction of this model requires the following steps: First, the azimuth data of the sun in different months and at different time points in the region need to be collected. The azimuth reflects the change in the angle of the sun relative to the horizon. These data can be obtained by querying the data of the observatory in the region, or they can be simulated and generated by astronomical calculation software. It is necessary to cover the azimuth data of different months of the year, different days of the month, and different time points of the day in the region. This provides basic data support for the movement of the sun for the subsequent modeling. Select an open ground in the photovoltaic power station and set a measuring benchmark with a height of about 0.5-1 meter. In different months and different time periods, control the camera to shoot the benchmark to obtain the image data of the shadow. The length and direction of the shadow reflect the azimuth information of the sun at that time. Try to shoot multiple shadow images of various lengths and angles. Match the solar azimuth data with the shadow image. Since the shadow azimuth is known, the azimuth of the sun can be calculated, and the optimal angle of the photovoltaic panel to the sun at this time can be inferred. This constitutes a training data set of input shadow images and corresponding optimal angles. The shadow image dataset and optimal angle dataset obtained in the previous step can be used to train the deep learning model. Here, you can choose a convolutional neural network to train the network model through the back-propagation algorithm so that it can infer the optimal angle of the photovoltaic panel from the shadow image. You can also set a validation set to evaluate the training effect and iterate the training until the model meets the accuracy requirements.

[0038] The shadow benchmark analysis model obtained already contains the mapping relationship between shadows and photovoltaic panel angles in various situations in the region throughout the year. Deploy it to the actual light-chasing system, input geography, time and shadow images in real time, and the model can quickly predict the current optimal photovoltaic panel adjustment parameters to achieve accurate light-chasing. By building a deep learning model and making full use of a large amount of measured shadow image data training, shadow features can be extracted with high precision, and a machine learning mapping between input and photovoltaic panel parameter output can be established to achieve intelligent decision-making from shadow benchmarks to light-chasing control, so that the light-chasing system has strong adaptability and decision-making capabilities.

[0039] S105, sending a control instruction to a motor corresponding to the photovoltaic bracket according to the adjustment parameters of the photovoltaic panel, so that the photovoltaic panel automatically faces the sun.

[0040] The photovoltaic panel adjustment parameters are the results output by the shadow benchmark analysis model, which reflects the angle or orientation information that the photovoltaic panel needs to adjust. The motors corresponding to the photovoltaic bracket usually include horizontal rotation motors and vertical pitch motors, which work together to achieve precise angle adjustment of the photovoltaic panel in a two-dimensional plane. These motors need to have high torque output capacity and precise position control accuracy to meet the adjustment requirements of the photovoltaic panel under different working conditions. After obtaining the photovoltaic panel adjustment parameters, the light chasing control system will perform a series of preprocessing and conversion on the parameters. Since the control of the motor is usually based on a specific electrical signal format and motion control protocol, it is necessary to convert the adjustment parameters into command signals that the motor driver can recognize. In the process of sending control instructions, precise time synchronization and signal transmission mechanisms are adopted. To ensure that the motor can accurately and synchronously perform the adjustment action, the control system uses an internal clock or an external synchronization signal source to accurately calibrate the time of instruction sending. After receiving the control instruction, the motor driver drives the motor to operate according to the instruction content. In the motor startup phase, soft start technology is used to gradually increase the power supply voltage and current of the motor to avoid excessive impact current and torque caused by instantaneous start of the motor, thereby reducing mechanical damage to the motor and transmission mechanism and extending the service life of the equipment. During the operation of the motor, the motor driver monitors the operating status of the motor in real time, including key parameters such as speed, current, and temperature. Through closed-loop control algorithms, such as PID control, the actual operating status of the motor is compared with the target status, and the motor supply voltage or current is adjusted in real time according to the deviation to achieve high-precision position control. As the photovoltaic panel rotates, the control system continuously monitors the position feedback information of the photovoltaic panel, usually obtained through a position sensor installed on the photovoltaic panel or the motor shaft. Once the photovoltaic panel reaches the predetermined adjustment position, the control system sends a stop command to the motor driver to stop the motor. At this time, the photovoltaic panel is accurately facing the sun, achieving the best lighting angle, thereby improving the efficiency of photovoltaic power generation and making full use of solar energy resources.

[0041] In some embodiments, before this step, the system uses a wind speed sensor to obtain wind speed data and wind direction data as a key basis for judging whether the current environment is suitable for light chasing. Specifically, the wind speed sensor is usually installed in a suitable position near the photovoltaic panel, and its working principle is based on aerodynamics or other relevant physical principles. It can accurately sense the flow speed of the surrounding air and convert it into a corresponding electrical signal or digital signal so that the light chasing control system can quickly and accurately read the wind speed data. At the same time, the sensor also has the function of detecting the wind direction. Through a specific structural design or with the help of an auxiliary wind direction measurement component, it can determine the direction of the wind and transmit the wind direction information to the control system in a prescribed format. When the wind speed data is obtained, the system will immediately compare it with the preset wind speed threshold. This preset wind speed threshold is derived from a large number of experiments and practical experience. Considering the mechanical structure strength and stability of the photovoltaic panel and the light chasing device, as well as the vibration and offset that may occur at different wind speeds, a safe and reasonable wind speed upper limit is determined in the system design stage. In addition to wind speed, wind direction data is also critical. The system will analyze the relationship between wind direction data and the current light chasing direction. The light-chasing direction is calculated based on the relationship between the azimuth of the sun and the position of the photovoltaic panel, aiming to enable the photovoltaic panel to always aim at the sun to obtain the maximum light intensity. If the wind direction data shows that the wind direction is opposite to the light-chasing direction, even if the wind speed does not exceed the preset threshold, it will have an adverse effect on the light-chasing effect. In the case of headwind, the motor needs to overcome greater resistance to rotate the photovoltaic panel, which will significantly increase energy consumption. Moreover, headwind may cause the photovoltaic panel to become unstable during the adjustment process, affecting its precise positioning and reducing power generation efficiency. When the system determines that the wind speed data is greater than the preset wind speed threshold, or the wind direction data is opposite to the light-chasing direction, it will quickly make a decision to suspend the current light-chasing control and keep the current position of the photovoltaic panel unchanged. The purpose of this is to protect the equipment from damage caused by severe weather conditions and avoid unnecessary energy waste and equipment loss. During the suspension of light-chasing control, the system will continue to monitor the wind speed and wind direction data. Once the environmental conditions return to the range suitable for light-chasing, that is, the wind speed is lower than the threshold and the wind direction no longer has a significant adverse effect on light-chasing, the system will automatically restart the light-chasing program to ensure that the photovoltaic panel can track the sun in a timely and accurate manner and achieve efficient photovoltaic power generation.

[0042] In the embodiment of the present application, the local geographic and time information is obtained as the basis for light chasing, and multiple light sensors are combined to accurately monitor the light intensity to trigger the image acquisition process. The shadow image is obtained by using the photovoltaic panel center measurement benchmark and high-definition image acquisition equipment, and the shadow benchmark analysis model based on the local annual solar azimuth change law and a large amount of measured data training is input, and finally a high-precision motor is driven to adjust the photovoltaic panel. Therefore, the problem of the inability to accurately track the sun's position due to the single information and insufficient accuracy in traditional photovoltaic light chasing methods, as well as the insufficient utilization of solar energy and low power generation efficiency caused by this, is effectively solved, thereby achieving the technical effect of high-precision tracking of the sun by photovoltaic panels, significantly improving photovoltaic power generation efficiency, and making full use of solar energy resources.

[0043] In some embodiments, the system uses an image acquisition device installed on or around the photovoltaic panel to monitor the status of the photovoltaic bracket in real time. When the user terminal issues a bracket status viewing instruction, the system will respond quickly and send the currently monitored photovoltaic bracket status information to the user terminal for display. The user terminal can be a computer, mobile phone application or other intelligent terminal device connected to the light chasing control system. Through these devices, the user can intuitively see the real-time image of the photovoltaic bracket or the processed status report, including the position, angle, whether there is any abnormality and other information of the bracket. This function allows users to understand the operating status of the photovoltaic equipment at any time without going to the site in person, greatly improving the convenience and efficiency of management. In addition, the system also has the function of receiving photovoltaic panel adjustment instructions sent by the user terminal, and can adjust the photovoltaic panel accordingly according to these instructions. The user may want to manually adjust the angle or position of the photovoltaic panel based on specific needs or analysis of the current power generation situation. When the user enters the adjustment instruction at the user terminal, the instruction will be transmitted to the light chasing control system through the network or other communication methods. After receiving the instruction, the system will verify the legality and rationality of the instruction to ensure that the instruction will not cause abnormal or dangerous conditions in the equipment. For example, if the adjustment angle input by the user exceeds the mechanical limit range of the photovoltaic panel, the system will refuse to execute the instruction and feedback an error message to the user. After confirming that the instruction is valid, the system will recalculate the adjustment parameters of the photovoltaic panel according to the instruction requirements and send a new control instruction to the motor to drive the motor to adjust the photovoltaic panel to the specified position or angle. This combination of manual adjustment by the user and automatic light tracking by the system enables the photovoltaic system to better adapt to various complex practical application scenarios, meet the diverse needs of users, and further improve the practicality and flexibility of the system.

[0044] After combining the above content, the following is a more detailed description of the process of the method provided by this implementation. Figure 2 , is another flow chart of the intelligent light tracking control method for a photovoltaic bracket in an embodiment of the present application.

[0045] S201, constructing a photovoltaic panel historical adjustment data set to record in real time the adjustment parameters of the photovoltaic panel in a certain period of time in the past; The historical adjustment data set refers to the collection of various related data involved in each adjustment operation of the photovoltaic panel in the past. The adjustment parameters cover the key information of the photovoltaic panel during the position adjustment process, including but not limited to the horizontal rotation angle, which determines the rotation amplitude of the photovoltaic panel on the horizontal plane relative to the initial position to accurately control its orientation toward the sun; the vertical pitch angle, which is used to adjust the tilt of the photovoltaic panel in the vertical plane to ensure better reception of sunlight at different altitudes; the timestamp of the adjustment, which accurately records the specific time when each adjustment operation occurs, so as to analyze the regularity of the adjustment operation in the time series; and the environmental information at that time, such as light intensity, which directly affects the startup and adjustment strategy of the light chasing system.

[0046] The light-chasing control system uses its internal storage mechanism and data acquisition function to construct the data set. The system first determines a specific time interval, and the length of this time can be reasonably set according to the system's storage capacity, data processing capabilities, and the needs of the actual application scenario. During this time period, whenever the adjustment operation of the photovoltaic panel is triggered, the system will obtain accurate adjustment parameter information through communication with the motor control system. For horizontal and vertical angle adjustments, the motor control system will feedback the current number of motor rotation steps or angle values, which are recorded after conversion and calibration. The timestamp is provided by the system's built-in high-precision clock module to ensure the accuracy of time recording, which can be accurate to seconds or even milliseconds. The collection of environmental information relies on various sensors distributed around the photovoltaic panel. Light intensity sensors usually use photosensitive elements such as photodiodes or photoresistors, which can change their own electrical characteristics according to changes in light intensity, thereby generating corresponding electrical signals. The system converts these signals into light intensity values ​​for recording. Temperature sensors are mostly based on the principles of thermistors or thermocouples, which can change resistance values ​​or generate thermoelectric potentials as ambient temperature changes, and are then converted into temperature data by the system. The humidity sensor uses the characteristics of capacitance or resistance changing with humidity to measure the air humidity. During the data collection process, the system will perform real-time verification and preprocessing on the collected data.

[0047] S202, analyzing the photovoltaic panel historical adjustment data set to generate a photovoltaic panel adjustment range model; The light-chasing control system will conduct a detailed analysis of the horizontal rotation angles in the historical adjustment data set, and calculate the mean, standard deviation, maximum and minimum values ​​of these angle data through statistical methods. For example, in the long-term data accumulation, it is found that the mean of the horizontal rotation angle is 30 degrees, the standard deviation is 5 degrees, the minimum is 10 degrees, and the maximum is 50 degrees. This shows that in most cases, the adjustment of the photovoltaic panel in the horizontal direction fluctuates around 30 degrees, and usually does not exceed the range of 10 to 50 degrees. Further application of data fitting techniques, such as least squares fitting, may find that the horizontal rotation angle shows a certain linear or nonlinear trend with time or light intensity. If in certain specific time periods, such as the morning period, the horizontal rotation angle shows a trend of gradually increasing over time, and conforms to the quadratic function relationship. This provides an important basis for the system to predict the reasonable range of the horizontal adjustment angle of the photovoltaic panel in similar time periods.

[0048] Similar analysis methods are also used for the vertical pitch angle. After calculating its statistical characteristic value, its association with environmental factors is further explored. The analysis found that during the high temperature period in summer, due to the high solar altitude angle, the vertical pitch angle of the photovoltaic panel is relatively small, mostly concentrated between 20 and 30 degrees; while in winter, the solar altitude angle is low, and the vertical pitch angle is larger, usually in the range of 40 to 60 degrees. In addition, when the light intensity is strong, the vertical pitch angle will approach a relatively stable value to ensure the best lighting effect. By constructing a multivariate regression model, taking factors such as light intensity, season, and time as independent variables, and the vertical pitch angle as the dependent variable, it is possible to accurately quantify the degree of influence of each factor on the vertical pitch angle, thereby determining the reasonable value range of the vertical pitch angle under different conditions.

[0049] In terms of timestamps, the system analyzes the distribution of adjustment operations in the time series. Using the time series analysis method, it is found that there are obvious peak and trough periods in the adjustment of photovoltaic panels within a day. For example, the number of adjustments is more frequent from 9 to 11 in the morning and from 2 to 4 in the afternoon, which is consistent with the rapid change in the position of the sun in these two periods. Around 12 noon and in the evening, the number of adjustments is relatively small. Based on this, the system can set different adjustment frequency expectations for different time intervals. When the actual adjustment frequency deviates from the expected range, an early warning will be issued in time to indicate that there may be abnormal conditions.

[0050] Based on the above analysis results of key data such as horizontal rotation angle, vertical pitch angle and timestamp, the light chasing control system uses machine learning algorithms, such as decision tree algorithm or support vector machine algorithm, to build a photovoltaic panel adjustment range model. The decision tree algorithm can classify and define the reasonable range of photovoltaic panel adjustment parameters according to different environmental conditions and historical data characteristics.

[0051] S203, inputting the target time period into the photovoltaic panel adjustment range model to obtain a reasonable variation range of the photovoltaic panel adjustment parameters; When the light-chasing control system needs to determine the reasonable variation range of the photovoltaic panel adjustment parameters within the current target time period, the constructed photovoltaic panel adjustment range model will be called.

[0052] The system will first perform accurate feature extraction for the target time period. The extracted features include seasonal information for the time period, such as summer, winter, spring, or autumn, because the sun's trajectory and illumination angle vary greatly in different seasons, which has a significant impact on the adjustment parameters of the photovoltaic panels. At the same time, the system will also obtain specific time period information for the time period during the day, such as early morning, morning, noon, afternoon, or evening, which is also closely related to the position of the sun and changes in light intensity. In addition, the system will also refer to current environmental information, such as real-time light intensity data, temperature, humidity, etc. These factors will indirectly affect the performance of the photovoltaic panels and the optimal adjustment angle.

[0053] After these feature data are input into the photovoltaic panel adjustment range model, the model will perform calculations and inferences based on its internal algorithms and pre-trained rules. If the target time period is in the morning period in summer, and the light intensity is strong and the temperature is high, the model will analyze the adjustment parameter range of photovoltaic panels under similar conditions in historical data. It is assumed that in the previous summer morning strong light and high temperature environment, the horizontal rotation angle usually varies between 25 degrees and 35 degrees, and the vertical pitch angle fluctuates between 15 degrees and 25 degrees. The model will output that the reasonable range of the horizontal rotation angle of the photovoltaic panel in the current target time period is approximately 25 degrees to 35 degrees, and the reasonable range of the vertical pitch angle is 15 degrees to 25 degrees.

[0054] In order to ensure the accuracy and reliability of the output results, the model will also conduct a certain confidence assessment. By analyzing the distribution of historical data under similar conditions and the prediction accuracy of the model, the confidence level of each adjustment parameter range is calculated. If the confidence level is lower than the preset threshold, the system may further collect more data or re-analyze historical data to optimize and adjust the model to improve the reliability of the prediction. After obtaining the reasonable range of changes in the adjustment parameters of the photovoltaic panel, the system will store this information in a temporary cache area so that it can be quickly called later when judging whether the actual adjustment parameters are reasonable. At the same time, the system will continue to monitor the operating status of the environment and photovoltaic panels. When the environmental conditions change significantly or the system detects abnormal conditions that may affect the adjustment of the photovoltaic panels, the characteristic data of the target time period will be updated in time and re-entered into the model to dynamically obtain the latest reasonable range of changes in the adjustment parameters to ensure that the photovoltaic panels can always operate within the optimal adjustment range and achieve efficient light chasing and power generation effects.

[0055] S204, determining whether the photovoltaic panel adjustment parameter exceeds the reasonable variation range; After obtaining the adjustment parameters of the current photovoltaic panel and the corresponding reasonable range of change output by the photovoltaic panel adjustment range model, the light chasing control system immediately starts the judgment process. The system first extracts the horizontal rotation angle value in the current adjustment parameter and compares it with the lower and upper limits of the horizontal angle in the previously determined reasonable range of change. In addition to simple numerical comparison, the system also considers the rate of change of the adjustment parameters. If the horizontal rotation angle or vertical pitch angle of the photovoltaic panel changes dramatically in a short period of time, even if the current value is still within a reasonable range, but the rate of change exceeds the threshold set based on historical data and physical laws, the system will mark it as an abnormal situation.

[0056] In addition, the system will make a comprehensive judgment based on the data from the environmental sensors. When the light intensity changes suddenly and significantly, such as when clouds quickly block the sun and cause a sudden drop in light intensity, the adjustment parameters of the photovoltaic panels may fluctuate briefly. The system will determine whether the current adjustment parameter changes are within a reasonable fluctuation range based on the preset light intensity change and adjustment parameter relationship model. If it exceeds this range, even if the parameter may be in a reasonable range under stable lighting conditions, it will be judged as abnormal in the current dynamic environment.

[0057] If the photovoltaic panel adjustment parameter does not exceed the reasonable variation range, executing step S205; If the photovoltaic panel adjustment parameter exceeds the reasonable variation range, step S206 is executed.

[0058] S205: Do not redetermine the photovoltaic panel adjustment parameters; If the PV panel adjustment parameters do not exceed the reasonable range of variation, the system will first record the status information that the current adjustment parameters are within the normal range, and store it in the operation log for subsequent data analysis and system maintenance personnel to view.

[0059] S206, re-determining the photovoltaic panel adjustment parameter so that the photovoltaic panel adjustment parameter is within a reasonable variation range; When the light-chasing control system determines that the adjustment parameters of the photovoltaic panel are beyond the reasonable range of variation, the system first traces back to the previously acquired historical adjustment data set of the photovoltaic panel and the current environmental data. Analyze the adjustment parameters of the photovoltaic panel in history under similar environmental conditions, find possible reference values, and preliminarily determine a new candidate range for the adjustment parameters. At the same time, the system will optimize based on the actual power generation efficiency data of the current photovoltaic panel. If the current power generation efficiency is low and the adjustment parameters that are beyond the reasonable range are considered to be one of the reasons for the decline in efficiency, the system will try to fine-tune the adjustment parameters based on the reference historical data.

[0060] S207, after obtaining the current power generation data of the photovoltaic panel in real time, input the current power generation data and the photovoltaic panel adjustment parameters into a pre-set photovoltaic power generation prediction model to predict the adjusted power generation prediction value, wherein the photovoltaic power generation prediction model is trained in advance based on a plurality of historical photovoltaic panel adjustment parameter combinations under different seasons, different weather conditions, and different time periods and the corresponding actual power generation data; The light-chasing control system is closely connected to the power monitoring module of the photovoltaic panel to obtain the current power generation data in real time. Subsequently, these data are input into the photovoltaic power generation prediction model that has been carefully constructed in advance. The construction of this model is based on a large amount of historical data, covering the differences in solar radiation in different seasons, such as the strong and long light intensity when the solar altitude angle is high in summer, and the opposite in winter; the changes in light under different weather conditions, the stable solar radiation on sunny days, and the light will be weakened to varying degrees on cloudy, cloudy or rainy days; and the impact of the change in the position of the sun in different time periods on the light received by the photovoltaic panel, such as the gradual increase in the solar altitude angle in the morning and the gradual decrease in the afternoon. During the training process, advanced machine learning algorithms such as deep neural network algorithms are used. The deep neural network performs complex feature extraction and nonlinear transformation on the input data through multiple hidden layers. It can automatically learn the deep relationship between the adjustment parameters of the photovoltaic panel and the power generation. For example, when the horizontal rotation angle is within a certain range and the vertical pitch angle is properly matched, the power generation in a specific season and weather conditions will reach the optimal level. The model also uses cross-validation and other techniques during training, dividing historical data into training sets, validation sets, and test sets, and continuously adjusting the model parameters to improve the model's generalization ability and prediction accuracy.

[0061] When the current power generation data and adjustment parameters are input, the model calculates according to its internal complex structure and learned rules. It first standardizes the input adjustment parameters to make them conform to the input feature scale during model training. Then, through a series of neuron calculations and weight matrix multiplications, combined with the current power generation data, it predicts the power generation forecast value in the next period of time if it continues to operate according to the current adjustment parameters.

[0062] S208, comparing the power generation forecast value with the actual power generation before adjustment, and calculating the power generation increase value; After obtaining the predicted power generation value, the light-chasing control system quickly calls out the actual power generation data before adjustment from the storage module. This data is recorded during the stable power generation stage before the last parameter adjustment on the photovoltaic panel. The system subtracts the actual power generation before adjustment from the predicted power generation value to obtain the difference between the two. This difference is the preliminary calculation result of the power generation improvement value. However, in order to more accurately evaluate the improvement effect, the system will also take into account some other factors. For example, by calculating the proportional relationship between the improvement value and the actual power generation before adjustment, that is, the relative improvement value, the relative improvement value can be used to more intuitively understand the impact of the adjustment parameters on the power generation.

[0063] S209: If the power generation increase value is lower than the preset minimum increase value, it is determined that the current light chasing control strategy is not effective, and the photovoltaic panel adjustment parameters are re-determined.

[0064] When the light-chasing control system finds that the power generation increase value is lower than the preset minimum increase value after calculation and analysis, it immediately triggers the re-evaluation of the current light-chasing control strategy and the re-determination of the adjustment parameters. The system will first generate a detailed analysis report, which includes the current power generation data, adjustment parameters, power generation forecast values, calculated increase values, and comparisons with the preset minimum increase values. At the same time, it will also attach recent environmental data change curves, such as changes in light intensity over time, fluctuations in temperature and humidity, etc., in order to fully understand the factors that may affect power generation efficiency. Then, the system goes back to the previous photovoltaic panel historical adjustment data set and power generation records. Find the adjustment parameter combination that can achieve a higher power generation increase under similar environmental conditions as a reference. This process is similar to case retrieval in data mining. By screening and analyzing a large amount of historical data, the most valuable cases are found, and their adjustment parameters and corresponding power generation changes are extracted. Then, according to the analysis results and processing conditions, the adjustment parameters are gradually adjusted. A small step adjustment strategy may be adopted, such as fine-tuning the horizontal rotation angle and vertical pitch angle by 0.5 degrees each time, while closely monitoring the changes in power generation. After each adjustment, the power generation increase value is recalculated until an adjustment parameter combination is found that enables the power generation increase value to reach or exceed the preset minimum increase value.

[0065] In the embodiments of the present application, due to the technical means of constructing a historical adjustment data set of photovoltaic panels and generating an adjustment range model to judge and optimize the adjustment parameters, and combining the power generation prediction model to evaluate and readjust the light chasing control strategy, the problems of unstable power generation efficiency, increased risk of equipment loss and insufficient energy utilization caused by the lack of effective verification and optimization mechanism in the adjustment process of photovoltaic panels are effectively solved, thereby achieving the technical effect of accurately controlling the adjustment parameters of photovoltaic panels, continuously improving power generation efficiency, ensuring stable operation of equipment and maximizing the utilization of solar energy resources.

[0066] The light tracking control system in the embodiment of the present invention is described below from the perspective of hardware processing. Figure 3 , which is a schematic diagram of a physical device structure of a light chasing control system in an embodiment of the present application.

[0067] It should be noted that Figure 3 The structure of the light chasing control system shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0068] like Figure 3 As shown, the light chasing control system includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 302 or the program loaded from the storage part 308 to the random access memory (RAM) 303, such as executing the method described in the above embodiment. In RAM 303, various programs and data required for system operation are also stored. CPU 301, ROM 302 and RAM 303 are connected to each other through bus 304. Input / output (I / O) interface 305 is also connected to bus 304.

[0069] The following components are connected to the I / O interface 305: an input section 306 including an audio input device, a button switch, etc.; an output section 307 including a liquid crystal display (LCD) and an audio output device, an indicator light, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as needed. A removable medium 311, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 310 as needed so that a computer program read therefrom is installed into the storage section 308 as needed.

[0070] In particular, according to an embodiment of the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication part 309, and / or installed from a removable medium 311. When the computer program is executed by the central processing unit (CPU) 301, various functions defined in the present invention are performed.

[0071] It should be noted that specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, apparatus, or device.

[0072] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. Each box in the flowchart or block diagram may represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the box may also occur in an order different from that marked in the accompanying drawings.

[0073] Specifically, the light-chasing control system of this embodiment includes a processor and a memory. The memory stores a computer program. When the computer program is executed by the processor, the intelligent light-chasing control method for the photovoltaic bracket provided in the above embodiment is implemented.

[0074] As another aspect, the present invention further provides a computer-readable storage medium, which may be included in the light-chasing control system described in the above embodiment; or may exist independently without being assembled into the light-chasing control system. The above storage medium carries one or more computer programs, and when the above one or more computer programs are executed by a processor of the light-chasing control system, the light-chasing control system implements the photovoltaic bracket intelligent light-chasing control method provided in the above embodiment.

[0075] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0076] As used in the above embodiments, the term "when..." may be interpreted to mean "if..." or "after..." or "in response to determining..." or "in response to detecting...", depending on the context. Similarly, the phrases "upon determining..." or "if (the stated condition or event) is detected" may be interpreted to mean "if determining..." or "in response to determining..." or "upon detecting (the stated condition or event)" or "in response to detecting (the stated condition or event)", depending on the context.

[0077] Those skilled in the art can understand that to implement all or part of the processes in the above-mentioned embodiments, the processes can be completed by computer programs to instruct related hardware, and the programs can be stored in computer-readable storage media. When the programs are executed, they can include the processes of the above-mentioned method embodiments. The aforementioned storage media include: ROM or random access memory RAM, magnetic disk or optical disk and other media that can store program codes.

Claims

1. A photovoltaic bracket intelligent light-chasing control method, applied to a light-chasing control system, characterized in that: The method comprises: Get local geographic information and current time information; Get the current light intensity through multiple light sensors; If the light intensity exceeds a preset start threshold, multiple image acquisition devices on the photovoltaic panel are controlled to capture the shadow of a measuring pole placed at the center of the photovoltaic panel to obtain shadow image data; The geographic information, the current time information and the shadow image data are input into a shadow benchmark analysis model to determine the photovoltaic panel adjustment parameters. The shadow benchmark analysis model is constructed by using a deep learning algorithm training in advance based on the local sun's azimuth angle variation law in different seasons and different time periods, and in combination with a plurality of measured benchmark shadow data and corresponding preset photovoltaic panel optimal power generation angle data; According to the photovoltaic panel adjustment parameters, a control instruction is sent to the motor corresponding to the photovoltaic bracket, so that the photovoltaic panel automatically faces the sun.

2. The method according to claim 1, characterized in that Before sending a control instruction to the motor according to the photovoltaic panel adjustment parameters so that the photovoltaic panel faces the sun, the method further includes: Construct a historical adjustment data set for photovoltaic panels to record the adjustment parameters of photovoltaic panels in real time over a certain period of time in the past; Analyzing the photovoltaic panel historical adjustment data set to generate a photovoltaic panel adjustment range model; Inputting the target time period into the photovoltaic panel adjustment range model to obtain a reasonable variation range of the photovoltaic panel adjustment parameters; Determining whether the photovoltaic panel adjustment parameter exceeds the reasonable variation range; If it exceeds the reasonable variation range, the photovoltaic panel adjustment parameter is re-determined to make the photovoltaic panel adjustment parameter within the reasonable variation range.

3. The method according to claim 2, characterized in that If the adjustment parameters of the photovoltaic panels are beyond the reasonable range, after the step of re-determining the adjustment parameters of the photovoltaic panels so that the adjustment parameters of the photovoltaic panels are within the reasonable range, the method further includes: After obtaining the current power generation data of the photovoltaic panel in real time, the current power generation data and the photovoltaic panel adjustment parameters are input into a pre-set photovoltaic power generation prediction model to predict the adjusted power generation prediction value, wherein the photovoltaic power generation prediction model is trained in advance based on a plurality of historical photovoltaic panel adjustment parameter combinations under different seasons, different weather conditions, and different time periods and the corresponding actual power generation data; Compare the predicted power generation value with the actual power generation before adjustment to calculate the power generation increase value; If the power generation increase value is lower than the preset minimum increase value, it is determined that the current light chasing control strategy is not effective, and the photovoltaic panel adjustment parameters are re-determined.

4. The method according to claim 1, characterized in that: Before the step of obtaining the current light intensity through multiple light sensors, it also includes: Obtain real-time power data of batteries in photovoltaic systems; A lookup table is pre-established showing the correspondence between battery power and the number of light chasing times; Querying the lookup table to obtain the number of light chasing times corresponding to the real-time power data; If the time interval between two light chasing controls is less than the preset minimum time interval, the number of light chasing times is modified to the number of times that the time interval between two light chasing controls is greater than or equal to the preset minimum time interval; Determine the light chasing time and frequency according to the modified light chasing times.

5. The method according to claim 1, characterized in that Before sending a control instruction to a motor corresponding to the photovoltaic bracket according to the photovoltaic panel adjustment parameters so that the photovoltaic panel automatically faces the sun, the method further includes: Obtain wind speed data and wind direction data through wind speed sensors; If the wind speed data is greater than a preset wind speed threshold, or the wind direction data is opposite to the light chasing direction, it is determined that the current environment is not suitable for light chasing, the current light chasing control is suspended, and the position of the photovoltaic panel is kept unchanged.

6. The method according to claim 1, characterized in that After sending a control instruction to a motor corresponding to the photovoltaic bracket according to the photovoltaic panel adjustment parameters so that the photovoltaic panel faces the sun, the method further includes: Real-time monitoring of the photovoltaic support status by the image acquisition device; After receiving the bracket status viewing instruction sent by the user end, the photovoltaic bracket status is sent to the user end for display; A photovoltaic panel adjustment instruction sent by the user end is received, and the photovoltaic panel is adjusted according to the photovoltaic panel adjustment instruction.

7. The method according to claim 1, characterized in that If the illumination intensity exceeds a preset start threshold, after the step of controlling multiple image acquisition devices on the photovoltaic panel to capture the shadow of the measuring pole to obtain shadow image data, the method further includes: If the shadow length of the measuring pole in the shadow image data is less than the set length, it is determined that the current position of the photovoltaic panel meets the power generation efficiency requirement, the photovoltaic panel position is kept unchanged, and the shadow pole analysis model is not used for light tracking control.

8. A server, characterized in that: The server includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the server to execute the method described in any one of claims 1-7.

9. A computer-readable storage medium comprising instructions, characterized in that: When the instructions are executed on a server, the server is caused to execute the method according to any one of claims 1 to 7.

10. A computer program product, characterized in that When the computer program product is run on a server, the server is caused to execute the method according to any one of claims 1 to 7.

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