Operation control method and system of solar cell panel

Abstract

The invention relates to the technical field of solar cell panel control, and discloses an operation control method and system for a solar cell panel, and the method comprises the steps: obtaining the specification information of the solar cell panel, setting the positioning information, carrying out the digital simulation according to the specification and positioning information, and generating a light receiving performance model and a sunlight environment model; generating a current-day illumination simulation model by combining seasonal and climatic factors by utilizing a historical database, analyzing the illumination simulation model and a light receiving performance model to obtain initial light receiving characteristics and a preset light receiving track, continuously recording illumination conversion electric energy of the cell panel to correct the preset light receiving track, and adjusting an inclination angle of the cell panel to obtain a current-day illumination simulation model. The energy conversion efficiency of the solar cell panel is improved, sunlight resources are fully utilized, different seasons and climate changes are adapted, the performance of the solar cell panel in a changing environment is enhanced, and the problem that in the prior art, the efficiency of collecting illumination data in real time for angle adjustment is low is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of solar panel control, and in particular to an operation control method and system of a solar panel. Background Art

[0002] In the past few years, solar power generation technology has made significant progress, especially the efficiency of photovoltaic panels has been continuously improved. However, due to the fact that the intensity, angle, duration and other factors of sunlight change at any time, the light receiving efficiency of solar panels is limited. Traditional solar panel systems usually use fixed inclination angles and directions, or simple tracking systems. Although this can improve the energy efficiency of solar panels to a certain extent, it does not take into account the long-term impact of various dynamic factors on the performance of solar panels.

[0003] In order to solve this problem, some modern intelligent light-chasing systems have been proposed. These systems can automatically adjust the inclination angle of the solar panel according to the change of solar radiation. However, these light-chasing systems generally only make simple adjustments based on the real-time sunlight intensity, and cannot predict the solar lighting environment of the day in advance based on historical data to obtain the corresponding light-chasing trajectory. As a result, the real-time adjusted solar panel inclination angle cannot take into account multiple aspects such as lighting effects, adjustment loss and equipment wear in the angle conversion between days. In addition, the solar panel inclination angle adjustment based only on the real-time collected sunlight data requires frequent changes in the angle, which lacks the efficiency of angle adjustment. Summary of the invention

[0004] The object of the present invention is to provide an operation control method and system for a solar panel, aiming to solve the problem of low efficiency in the prior art of collecting illumination data in real time for angle adjustment.

[0005] The present invention is implemented as follows. In a first aspect, the present invention provides an operation control method of a solar panel, comprising: Acquiring panel specification information and setting location information of the solar panel, and performing digital simulation analysis of panel performance and the sunlight environment in which the solar panel is located on the solar panel according to the panel specification information and the setting location information, so as to obtain a light receiving performance model and a sunlight environment model of the solar panel; According to the historical database, the seasonal elements and climatic elements of the current date are assigned to the daylight environment model to obtain a daylight simulation model based on the daylight environment model, and the daylight simulation model is combined with the light receiving performance model and analyzed to obtain the initial light receiving characteristics of the solar panel on the current day and the preset light receiving trajectory on the current day; wherein the initial light receiving characteristics of the current day are used to describe the inclination angle of the solar panel initially receiving light on the current date, and the preset light receiving trajectory on the current day is used to describe the change in the inclination angle of the solar panel receiving light that is expected to be planned to change with time on the current date; The solar panel is continuously recorded for converting sunlight into electrical energy on the current date to obtain a characteristic sequence of light reception of the solar panel on the current day, and a trajectory correction is performed on the preset light reception trajectory on the current day according to the characteristic sequence of light reception on the current day, so as to control the inclination angle of the solar panel according to the corrected preset light reception trajectory.

[0006] In a second aspect, the present invention provides an operation control system of a solar panel, which is used to implement an operation control method of a solar panel according to any one of the first aspects, including: A digital simulation module, used to obtain the panel specification information and setting location information of the solar panel, and perform digital simulation analysis of the panel performance and the sunlight environment of the solar panel according to the panel specification information and the setting location information, so as to obtain a light receiving performance model and a sunlight environment model of the solar panel; A trajectory analysis module, used to assign seasonal elements and climatic elements of the current date to the daylight environment model according to the historical database, so as to obtain a daylight simulation model based on the daylight environment model, and combine the daylight simulation model with the light receiving performance model for analysis to obtain the initial light receiving characteristics of the solar panel on the current day and the preset light receiving trajectory of the current day; wherein the initial light receiving characteristics of the current day are used to describe the inclination angle of the solar panel initially receiving light on the current date, and the preset light receiving trajectory of the current day are used to describe the change in the inclination angle of the solar panel receiving light that is expected to be planned to change with time on the current date; The trajectory correction module is used to continuously record the light-conversion electrical energy of the solar panel on the current date to obtain the light-receiving characteristic sequence of the solar panel on the current day, and to perform trajectory correction on the preset light-receiving trajectory of the current day according to the light-receiving characteristic sequence of the current day, so as to control the inclination angle of the solar panel according to the corrected preset light-receiving trajectory.

[0007] The present invention provides an operation control method of a solar panel, which has the following beneficial effects: The present invention obtains specification information and setting positioning information of a solar cell panel, performs digital simulation according to the specification and positioning information to generate a light receiving performance model and a daylight environment model, utilizes a historical database in combination with seasonal and climatic factors to generate a daylight simulation model, analyzes the light simulation model and the light receiving performance model to obtain initial light receiving characteristics and a preset light receiving trajectory, continuously records the light conversion electrical energy of the battery panel to correct the preset light receiving trajectory, adjusts the inclination angle of the battery panel, improves the energy conversion efficiency of the solar cell panel, makes full use of sunlight resources, adapts to different seasons and climate changes, enhances the performance of the solar cell panel in a changing environment, and solves the problem of low efficiency in real-time collection of light data for angle adjustment in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Figure 1 is a schematic diagram of steps of an operation control method of a solar panel provided by an embodiment of the present invention; Figure 2 It is a structural schematic diagram of an operation control system of a solar panel provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0009] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0010] The implementation of the present invention is described in detail below in conjunction with specific embodiments.

[0011] Reference Figure 1 , Figure 2 As shown, a preferred embodiment of the present invention is provided.

[0012] In a first aspect, the present invention provides an operation control method of a solar panel, comprising: S1: Obtaining panel specification information and setting location information of a solar panel, and performing digital simulation analysis on the panel performance and the sunlight environment of the solar panel according to the panel specification information and the setting location information, so as to obtain a light receiving performance model and a sunlight environment model of the solar panel; S2: assigning seasonal elements and climatic elements of the current date to the daylight environment model according to the historical database to obtain a daylight simulation model based on the daylight environment model, combining the daylight simulation model with the light receiving performance model and analyzing them to obtain the initial light receiving characteristics of the solar panel on the current day and the preset light receiving trajectory of the current day; wherein the initial light receiving characteristics of the current day are used to describe the inclination angle of the solar panel initially receiving light on the current date, and the preset light receiving trajectory of the current day are used to describe the change in the inclination angle of the solar panel receiving light that is expected to be planned to change with time on the current date; S3: continuously recording the light-conversion electrical energy of the solar panel on the current date to obtain the light reception characteristic sequence of the solar panel on the current day, and performing trajectory correction on the preset light reception trajectory on the current day according to the light reception characteristic sequence on the current day, so as to control the inclination angle of the solar panel according to the corrected preset light reception trajectory.

[0013] Specifically, in step S1 of the embodiment provided by the present invention, basic technical parameters of the solar panel are obtained to understand the performance characteristics of the panel, including collecting the main parameters of the panel, such as area (m²), efficiency, conversion efficiency, maximum power output (Wp), materials used (such as monocrystalline silicon, polycrystalline silicon, etc.), operating temperature range of the panel, etc., and electrical properties of the mobile phone panel, such as maximum power voltage (Vmp), open circuit voltage (Voc), maximum power current (Imp), short circuit current (Isc), etc., to obtain accurate panel performance data, provide a basis for subsequent simulation calculations, ensure that the panel efficiency calculation in the simulation process is accurate, so as to predict the actual working conditions.

[0014] More specifically, the installation position and angle of the solar panel are obtained. These factors directly affect the light reception effect. The installation position (longitude, latitude) and azimuth (i.e. the orientation of the panel, such as south, 15 degrees east of due south, etc.) of the solar panel are determined. The tilt angle of the solar panel (the angle formed with the ground) and whether automatic tracking adjustment is supported (for example, whether it is a single-axis tracking, dual-axis tracking system, etc.) are determined. The installation position and angle information of the solar panel is obtained, which is crucial to the subsequent sunshine model. The sun angle, light intensity, light distribution, etc. are closely related to the geographical location and azimuth.

[0015] More specifically, based on the geographical location and time characteristics of the solar panels, the solar radiation conditions in the area are simulated, and the radiation intensity and angle of the sun at different times of the day and throughout the year are calculated through geographic information (latitude and longitude) and time data (date, time). The sun's movement trajectory in a day is predicted using a solar trajectory model, including the sun's altitude and azimuth. The intensity of sunlight is further corrected by taking into account seasonal changes and climatic factors such as cloud cover, temperature, humidity and other factors.

[0016] It is understandable that building an accurate daylight environment model enables accurate simulation of the lighting conditions at the location of the panels. The model takes into account seasonal and climate change and can dynamically simulate changes in solar radiation in different time periods and climate conditions.

[0017] More specifically, a light receiving performance model of the panel is established based on the technical parameters of the panel and the sunlight environment in which it is located. According to the relationship between the photoelectric conversion efficiency of the panel and the angle, the power generation capacity of the panel at different times, different tilt angles and azimuths is calculated. Based on the specification information of the panel, a relationship model between the light receiving performance and the sunlight intensity and the angle of receiving light is established. The power generation at each moment is estimated through the photovoltaic effect model. The effects of factors such as temperature, pollution, and dust on the light receiving efficiency can also be considered to obtain an accurate light receiving performance model of the panel, which can predict how much electricity the panel can generate under specific lighting conditions. Combined with the technical characteristics of the panel, its optimal performance in various sunlight environments can be simulated.

[0018] More specifically, the daylight environment model and the solar panel light performance model are combined to make a comprehensive performance prediction, and the model is analyzed using computer simulation tools. These tools can simulate the working state of solar panels under different light, temperature, and weather conditions. According to the specifications and positioning information of the solar panels, the daylight environment model is combined with the solar panel light performance model to dynamically calculate the light intensity, angle, and power generation. In the simulation, the light changes at different time periods of the day, especially in the morning, afternoon, and evening, are considered to obtain accurate power generation prediction results of solar panels under specific environments and conditions, and simulate the performance of solar panels in different seasons, different geographical locations, and different weather conditions, helping to optimize the installation and operation parameters of solar panels.

[0019] Specifically, in steps S2 and S3 of the embodiment provided by the present invention, the movement trajectory of the sun and the light intensity in different seasons are calculated according to the current date and the geographical location, including the altitude angle (sun angle) and azimuth angle (sun position) of the sun in the sky. The historical meteorological data (such as cloud cover, temperature, humidity, wind speed, etc.) are used to assign values ​​to the daylight environment model to simulate the actual impact of the current weather on the light. The weather model can be calculated through real-time or historical meteorological data to correct the sunlight intensity and light quality. The seasonal data and climate data in the historical database are used to calculate the light intensity of the day, and the factors such as cloud cover, temperature, humidity, etc. are considered to obtain the sunlight simulation model of the day. The daylight environment model is corrected through historical data and real-time meteorological information to more accurately reflect the light conditions of the day, especially considering the impact of seasonal changes and climate changes on light, so as to provide a more accurate light simulation basis for the performance prediction of solar panels and avoid energy loss caused by seasonal changes or sudden climate changes.

[0020] More specifically, based on the supplemented daylight environment model, a light simulation model for the day is constructed to accurately predict the light intensity and angle at different time periods of the day. The sun's trajectory for the day is calculated based on the current date and geographic location, including the sun's altitude and azimuth. Combined with supplemented seasonal and climatic factors, the change in sunlight intensity over time is simulated. These data will describe the change process of the sun from dawn to dusk. Taking into account environmental changes (such as cloud changes, rain, etc.), the light intensity is further adjusted to obtain the real-time light simulation curve of the day. By accurately simulating the changes in sunlight on the day, accurate light input can be provided for the solar panel's light performance model to ensure the high accuracy of the simulation results. The dynamic simulation takes into account the weather and seasonal changes of the day and can provide more accurate light predictions.

[0021] More specifically, the day's illumination simulation model is combined with the solar panel's light reception performance model for comprehensive analysis to obtain the initial light reception characteristics and preset light reception trajectory of the solar panel on that day. The day's sunlight simulation model is combined with the panel's light reception performance model to analyze the panel's power generation efficiency under different light intensities and angles, and calculate the day's initial light reception characteristics. This characteristic describes the inclination angle of the panel when it initially receives light on that day, that is, at the beginning of the day (such as in the morning), the panel should set its angle for receiving light according to the current solar altitude and azimuth.

[0022] More specifically, the preset light-receiving trajectory for the day is calculated, and by analyzing the trend of sunlight changes on that day, it is predicted how the panels should gradually adjust their tilt angle over time to receive light in the best way. This ensures that the solar panels can accurately adjust their angles at the initial moment (such as early in the morning or just starting to work) to maximize the initial light reception. According to the changes in sunlight on that day, the angle adjustment plan of the panels is dynamically optimized to ensure that the solar panels can continue to receive light efficiently at all times of the day.

[0023] More specifically, by recording the light receiving characteristics of the solar panel in real time and comparing them with the preset light receiving trajectory, the angle control strategy of the solar panel is adjusted. In actual operation, the light reception situation of the solar panel is recorded in real time, its power output is monitored, the real-time light data is compared with the preset light receiving trajectory, and the preset trajectory is corrected to cope with possible changes (such as cloud cover, temperature changes, etc.). If there is a deviation (such as light changes faster or slower than expected), the tilt angle of the solar panel is dynamically adjusted to restore the optimal light reception effect, thereby improving the adaptability of the solar panel in actual operation. Through dynamic adjustment, sudden weather changes can be responded to, and light loss caused by deviations from the preset trajectory and the actual situation can be avoided. The light tracking accuracy of the solar panel is enhanced, so that the solar panel can maintain high efficiency in all-weather environments.

[0024] It is understandable that the tilt control strategy of the solar panel is optimized to ensure that the solar panel can receive light at the best angle under all weather conditions, input the corrected preset light-receiving trajectory into the control system of the solar panel, automatically adjust the tilt angle of the solar panel, and make real-time adjustments to the angle control system of the solar panel so that it can be adjusted according to the optimized trajectory to ensure that the solar panel is always in the best light-receiving state, thereby improving the overall power generation efficiency of the solar panel. By precisely controlling its angle, it can obtain the maximum amount of light under different weather and time conditions. Automated angle adjustment reduces manual intervention and improves the intelligence and adaptability of the system.

[0025] The present invention provides an operation control method of a solar panel, which has the following beneficial effects: The present invention obtains specification information and setting positioning information of a solar cell panel, performs digital simulation according to the specification and positioning information to generate a light receiving performance model and a daylight environment model, utilizes a historical database in combination with seasonal and climatic factors to generate a daylight simulation model, analyzes the light simulation model and the light receiving performance model to obtain initial light receiving characteristics and a preset light receiving trajectory, continuously records the light conversion electrical energy of the battery panel to correct the preset light receiving trajectory, adjusts the inclination angle of the battery panel, improves the energy conversion efficiency of the solar cell panel, makes full use of sunlight resources, adapts to different seasons and climate changes, enhances the performance of the solar cell panel in a changing environment, and solves the problem of low efficiency in real-time collection of light data for angle adjustment in the prior art.

[0026] Preferably, the steps of obtaining the panel specification information and the setting location information of the solar panel, and performing digital simulation analysis on the panel performance and the sunlight environment in which the solar panel is located according to the panel specification information and the setting location information to obtain the light receiving performance model and the sunlight environment model of the solar panel include: S11: Acquire the panel specification information of the solar panel; wherein the panel specification information includes the appearance specification information and the photoelectric conversion performance information of the solar panel; S12: performing digital simulation of the external structure of the solar cell panel according to the external shape specification information to obtain a simulation model of the light-receiving surface of the solar cell panel; S13: configuring the performance parameters of photoelectric conversion of the light-receiving surface simulation model according to the photoelectric conversion performance information to obtain the light-receiving performance model; S14: Acquire the setting and positioning information of the solar panel; wherein the setting and positioning information includes a description of the setting and positioning of the solar panel under multiple positioning standards, and the positioning standards include a latitude and longitude standard, an altitude standard, and a landform environment standard; S15: performing a multi-dimensional analysis of the basic receiving environment of sunlight at the location of the solar panel according to the setting positioning information, and obtaining the influencing factors and influencing weights of the setting positioning description under each positioning standard on the sunlight environment of the solar panel through the multi-dimensional analysis; S16: performing digital simulation analysis on the sunlight environment in which the solar panel is located according to various influencing factors and influencing weights to obtain a sunlight environment model of the solar panel.

[0027] Specifically, basic information of solar panels, including their appearance and photoelectric conversion performance, is obtained for subsequent performance analysis. The appearance specification information includes the size and shape of the panels, the arrangement of photovoltaic modules (for example, monocrystalline silicon, thin film, heterojunction, etc.) and the size of each photovoltaic unit. Photoelectric conversion performance information includes key performance parameters such as the photoelectric conversion efficiency, maximum power, open circuit voltage, short circuit current, etc. of the panels.

[0028] More specifically, ensure that the specification information of the solar panel is accurate and provide real and valid data as the basis for subsequent simulation analysis. The appearance specifications and photoelectric conversion performance information are necessary parameters for simulating the light receiving performance and photoelectric conversion efficiency of the solar panel.

[0029] More specifically, digital modeling of the outer structure is performed according to the outer specification information of the solar panel to obtain a simulation model of the light-receiving surface of the solar panel. CAD or other three-dimensional modeling software is used to create a digital model of the solar panel based on the acquired outer specification data of the solar panel, and the position and layout of the photovoltaic surface are determined. Taking into account factors such as the inclination angle and arrangement of the solar panel, a light-receiving surface model of the solar panel is generated, and an accurate three-dimensional model is generated, so that subsequent lighting and performance simulations are more in line with reality, and a preliminary analysis of the light reception effect of the solar panel shape is performed through digital simulation.

[0030] More specifically, according to the photoelectric conversion performance information of the solar panel, the photoelectric conversion performance parameters of the light-receiving surface simulation model are configured, and the photoelectric conversion performance information (such as conversion efficiency, maximum power point voltage and current, etc.) is input into the light-receiving surface simulation model. According to different light intensity, angle, temperature and other factors, the performance parameters of the solar panel are adjusted to simulate its output power and efficiency under actual working conditions. Through parameter configuration, it is possible to realize dynamic simulation of the performance of the solar panel under different light and environmental conditions, obtain a light-receiving performance model, accurately simulate the photoelectric conversion efficiency of the solar panel, and make the light-receiving performance model more realistic and operational.

[0031] More specifically, obtain the setting location information of the solar panel to ensure that the geographical location and environmental factors of the solar panel are taken into account during the simulation process. Longitude and latitude standards: obtain the longitude and latitude information of the location where the solar panel is installed. Altitude standards: obtain the altitude of the location where the solar panel is located. Geomorphic environment standards: understand the geomorphic environment around the solar panel, such as whether there are obstructions such as high buildings, mountains, and trees, as well as the lighting impact caused by the air quality associated with this geomorphic environment. Obtain complete positioning information to provide accurate geographic and environmental data for subsequent daylight environment model analysis. Positioning information helps to evaluate the impact of the environment in which the solar panel is located on sunlight, especially factors such as obstructions and terrain.

[0032] More specifically, according to the positioning information, analyze the impact of the location of the solar panel on the basic receiving environment of sunlight, analyze the latitude and longitude, calculate the changes in the position of the sun (such as the solar altitude angle and azimuth) and the changes in solar radiation intensity based on the longitude and latitude, and analyze the impact of altitude on the thickness of the atmosphere and the intensity of radiation. Generally, higher altitudes may receive stronger solar radiation. According to the topographic environment (such as buildings, hills, trees, etc.), analyze whether there are obstructions that affect the intensity of sunlight received by the solar panel. Through multi-dimensional analysis of the location of the solar panel, more accurate daylight environment simulation results can be obtained, and the impact of different environmental factors (such as longitude and latitude, altitude and topography) on the solar panel’s reception of sunlight can be accurately quantified, providing reliable basic data for subsequent simulations.

[0033] More specifically, based on the analysis results, the influencing factors and corresponding weights of various environmental factors on the sunlight reception of solar panels are calculated, and the influencing factors (such as latitude, altitude, terrain, obstructions, etc.) are combined with the influence weights (weight coefficients based on actual conditions). Through multi-dimensional analysis tools, the specific impact of each factor on light intensity is obtained, and the contribution of environmental factors to the sunlight reception effect of solar panels is accurately evaluated, which helps to optimize the installation and adjustment strategies of solar panels and provide a quantitative model to support subsequent optimization analysis and adjustments.

[0034] More specifically, the above-mentioned influencing factors and weights are applied to the daylight environment simulation to obtain the daylight environment model of the solar panel. According to the movement trajectory of the sun and the geographic positioning information of the panel, the intensity changes of solar radiation in different time periods are simulated, the degree of blocking of sunlight by obstructions such as surrounding terrain, buildings, and air quality is simulated, and the actual received light intensity is corrected. Combined with meteorological data, the influence of climate factors such as clouds and temperature on light intensity is analyzed. All influencing factors are comprehensively considered to construct a complete daylight environment model, and the lighting conditions of the panel under specific time and environment are simulated to obtain a dynamic and real-time daylight environment model that can reflect the lighting changes of solar panels under different time, seasons and climate conditions. The daylight environment model can provide a theoretical basis for optimizing the performance of the panel and ensure the efficient operation of the panel in different environments.

[0035] Preferably, the step of assigning seasonal elements and climatic elements of the current date to the daylight environment model according to the historical database to obtain a daylight simulation model based on the daylight environment model comprises: S21: Obtaining date information of the current date, and substituting the date information of the current date into a historical database to perform date positioning and historical data search, so as to obtain historical reference data of the current date; wherein the historical reference data includes ambient light data, seasonal characteristic data, and climate characteristic data of the solar panel in the adjacent dates; S22: extracting the characteristics of seasonal influence and climatic influence on the ambient light data of the solar panel, and obtaining the seasonal factors and climatic factors to which the solar panel is subjected on the current date; S23: assigning the seasonal elements and climatic elements of the current date to the daylight environment model, and allowing the daylight environment model to simulate the expected daylight environment of the current date according to the seasonal elements and climatic elements of the current date, so as to obtain a daylight simulation model based on the daylight environment model.

[0036] Specifically, obtain the accurate date information of the current date to determine the reference time point of seasonal and climatic data, obtain the current system date or obtain the current date through the input date information, extract the year, month and day of the current date, identify the corresponding season and related climate characteristics (such as spring, summer, autumn and winter, wet and dry seasons, etc.), ensure the accuracy of the date information, and provide the correct starting point for subsequent historical data search and simulation processing.

[0037] More specifically, the current date is used as a query condition to locate and obtain data for the corresponding date or nearby dates in the historical database to provide accurate historical background data for the simulation. The current date is substituted into the historical database, and relevant historical data is retrieved based on the date information. The lighting data, seasonal characteristic data, and climate characteristic data for nearby dates are found from the historical database. The nearby date data may include data from the days or weeks before and after. Depending on the actual storage method of the database, reference data that matches the current date environment can be extracted from the historical data to ensure that historical comparisons during the simulation process are based on real weather and seasonal patterns, thereby increasing the accuracy of the simulation and matching the seasonal and climatic data with the current date.

[0038] More specifically, key elements reflecting seasonal and climatic influences are extracted from historical data in order to accurately simulate the daylight environment of the current date, and information such as light intensity, sunshine duration, solar altitude angle, etc. related to seasonal changes in historical data are analyzed. Seasonal factors are usually related to changes in solar radiation, daylight duration, solar angle and other factors. The influence of climatic factors such as temperature, humidity, cloud cover, wind speed and other climatic factors on light intensity and distribution are extracted from historical data. Climatic influences may affect the amount of direct sunlight radiation, especially weather conditions such as cloudy, foggy or rainy days.

[0039] More specifically, by extracting seasonal and climatic elements, we can obtain data that accurately reflects the characteristics of the current daylight environment, ensuring that the simulation not only takes into account seasonal changes but also specific climatic conditions, providing accurate input data for subsequent simulations and helping the model reflect the actual impact of seasonal and climatic factors in the daylight environment simulation of the current date.

[0040] More specifically, the extracted seasonal and climatic elements are applied to the daylight environment model, and the environmental parameters in the model are corrected or adjusted to reflect the actual situation on the current date. The seasonal elements extracted from the historical reference data (such as seasonally changing light intensity, solar radiation angle, etc.) are input into the daylight environment model, and the climatic elements (such as current weather conditions, temperature, cloud coverage, etc.) are input into the daylight environment model to adjust the light intensity and distribution in the model. By adjusting the various parameters in the model, it is ensured that the model reflects the actual environment of the current date.

[0041] More specifically, the successful integration of seasonal and climatic elements into the model enables the daylight environment model to accurately simulate the lighting environment of the current date. The model is more precise and can reflect the specific impact of weather and seasonal changes on lighting conditions in real time, providing more realistic data support.

[0042] More specifically, based on the assigned seasonal and climatic elements, the daylight environment model is simulated to obtain the expected daylight environment for the current date. According to the settings of the daylight environment model, the solar radiation intensity, solar angle changes, cloud changes and other influencing factors on the current date are simulated. According to the current seasonal and climatic data, the light intensity, radiation pattern and shadow impact are dynamically adjusted to generate a daylight environment model that reflects the current actual conditions.

[0043] More specifically, the daylight environment model of the current date obtained through simulation processing can accurately reflect the lighting conditions of the day, helping decision makers understand the performance of solar panels on a specific date and environment. The daylight environment model can predict changes in solar radiation, temperature, humidity, etc. on the current date in real time, providing real-time environmental data support for subsequent panel performance optimization.

[0044] More specifically, the daylight environment model that has been corrected for seasonality and climate is used as the basis to generate the lighting simulation results for the day. Based on the corrected daylight environment model, dynamic simulation of light intensity, sunshine time, sun position, radiation angle, etc. is performed to output the lighting simulation results for the day, including key data such as light intensity distribution and changing trends.

[0045] More specifically, the final daily sunlight simulation model can accurately reflect the changes in sunlight on the day, help predict the power generation capacity and system performance of solar panels, provide accurate sunlight data for the scheduling, maintenance and optimization of solar power generation systems, and enhance the adaptability and efficiency of the system.

[0046] Preferably, the step of extracting the characteristics of seasonal influences on the ambient light data of the solar panel to obtain the seasonal factors to which the solar panel is subjected on the current date comprises: S221: determining the seasonal characteristics corresponding to the ambient light data of the solar panel according to the date information of the current date, and scheduling the seasonal impact identification standard corresponding to the seasonal characteristics; S222: extracting the characteristics of the influencing factors from the ambient light data of the solar panel according to the seasonal impact identification standard, so as to obtain the seasonal factors to which the solar panel is subjected on the adjacent dates; S223: Analyzing the difference relationship between the seasonal element of the solar panel on the current date and the seasonal element suffered by the solar panel on the adjacent date according to the date information of the current date, and performing difference correction processing on the seasonal element suffered by the solar panel on the adjacent date according to the difference relationship obtained by the analysis, so as to obtain the seasonal element suffered by the solar panel on the current date.

[0047] Specifically, extract the year, month, and day information of the current date, and determine the season (spring, summer, autumn, or winter) based on the current date. For example, spring: March 21st to June 20th, summer: June 21st to September 22nd, autumn: September 23rd to December 20th, and winter: December 21st to March 20th. Confirm the seasonal variation patterns corresponding to seasonal characteristics (such as light intensity, solar altitude angle, sunshine duration, etc.), determine the season of the current date, ensure that the seasonal feature extraction matches the actual environmental conditions, provide accurate background data for subsequent data analysis, and provide a clear framework for the identification of seasonal characteristics of light data, which is convenient for subsequent analysis and correction.

[0048] More specifically, the corresponding seasonal impact identification criteria are dispatched according to the determined seasonal characteristics, the influencing factors related to seasonal changes are identified, and appropriate seasonal impact criteria are selected according to the seasonal change characteristics. These criteria may include seasonal light intensity changes, solar altitude angle changes, sunshine duration changes, etc. These seasonal change factors are identified in the light data, and the corresponding impact identification model or algorithm is dispatched.

[0049] More specifically, by scheduling the seasonal impact identification standards, we can ensure that the seasonal changes in the lighting data can be accurately extracted for different seasonal change factors, and can effectively identify the impact of seasonal changes on factors such as light intensity and solar radiation angle, laying the foundation for subsequent feature extraction and difference analysis.

[0050] More specifically, features related to seasonal changes are extracted from the ambient lighting data to quantify the impact of seasonality on lighting. Based on the seasonal impact standard, seasonally related ambient lighting features are extracted. For example, in spring, there may be higher solar radiation and longer sunshine duration, and in winter, there may be lower solar radiation and shorter sunshine duration. These seasonal features, such as solar radiation intensity, solar altitude angle, daylight duration, etc., are extracted to make seasonal corrections to lighting.

[0051] More specifically, the extracted seasonal features can intuitively reflect the relationship between light intensity and seasonal changes, further help analyze the seasonal variation characteristics of light data, and provide key feature parameters for subsequent difference relationship analysis and correction.

[0052] More specifically, the differences between the seasonal elements of the current date and adjacent dates (such as a few days before and after) are analyzed in order to correct the seasonal elements, and seasonal characteristic data corresponding to the current date and adjacent dates (such as the previous day, the next day, or the previous week) are obtained. The seasonal elements of the current date (such as light intensity, sunshine duration, etc.) are compared with the seasonal elements of adjacent dates, and the differences between the two are analyzed. For example, the current date and adjacent dates may differ in light intensity, sunshine duration, etc. By analyzing these differences, the trend and degree of seasonal changes are determined.

[0053] More specifically, analyzing the differential relationships among seasonal elements can provide a clear understanding of the specific impact of seasonal changes on illumination, help the model to more accurately reflect the temporal changes in illumination data, provide a dynamic perspective, help understand the changing patterns of seasonal elements in different time periods, and provide a basis for subsequent corrections and adjustments.

[0054] More specifically, based on the seasonal difference relationship obtained from the analysis, the seasonal elements of adjacent dates are corrected to make them more consistent with the seasonal characteristics of the current date. The specific difference between the seasonal elements of the current date and the adjacent dates is calculated through difference relationship analysis. For example, if the solar radiation intensity of the current date is 10% higher than that of the adjacent date, adjustments are made to correct the seasonal elements of the adjacent dates, such as adjusting the light intensity, sunshine duration, etc., to make them consistent with the current seasonal characteristics. The corrected seasonal elements are confirmed and verified in combination with historical data and seasonal change trends to ensure that the corrected data accurately reflects the environment of the current date.

[0055] More specifically, after the difference correction, the seasonal impact of the current date can be accurately reflected, making the lighting data closer to the actual situation and increasing the accuracy of the simulation. Through the correction processing, the seasonal elements can dynamically adapt to the changes on different dates, ensuring the efficiency and accuracy of the seasonal correction.

[0056] More specifically, based on the above steps, the seasonal influencing factors of the solar panels on the current date are finally obtained. Combined with the seasonal factors after difference correction, the seasonal factors on the current date (such as light intensity, solar altitude angle, sunshine duration, etc.) are obtained. The seasonal factors are combined with other environmental factors (such as climatic characteristics) to provide detailed input data for the daylight environment model. The seasonal factors finally obtained can accurately reflect the seasonal environment of the solar panels on the current date, ensuring that the simulation results of the model are consistent with the actual situation. Accurate seasonal factors provide a basis for performance evaluation and optimization of solar panels, and help predict and adjust the power generation capacity and efficiency of the system.

[0057] Preferably, the step of extracting the features of the climate impact on the ambient light data of the solar panel to obtain the climate elements to which the solar panel is subjected on the current date comprises: S224: Acquire historical climate characteristics of adjacent dates and predicted climate characteristics of the current date through network communication; S225: extracting the features of the climate impact on the ambient light data of the solar panel according to the historical climate characteristics of the adjacent dates, so as to obtain the climate elements to which the solar panel is subjected on the adjacent dates; S226: Comparing the predicted climate characteristics with the historical climate characteristics to obtain a difference relationship between the predicted climate characteristics and the historical climate characteristics to which the solar panel is subjected on the current date, and performing element correction on the climate elements to which the solar panel is subjected on adjacent dates according to the difference relationship to obtain the climate elements to which the solar panel is subjected on the current date.

[0058] Specifically, accurate climate data is obtained to understand the climate conditions of the current date and nearby dates in order to extract and correct climate features. Network communication technology is used to obtain historical climate data of nearby dates (for example, temperature, humidity, precipitation, wind speed, etc.) and estimated climate data of the current date from meteorological data platforms (such as the National Meteorological Administration, weather forecast API, etc.). Ensure that the acquired data time range covers the current date and nearby dates (such as data from the previous few days), ensure that the data is accurate and real-time, and match the climate conditions of the area where the solar panels are located. The acquired climate data provides accurate background information for subsequent climate feature extraction, which helps to understand the impact of local climate change on the performance of solar panels. Network communication realizes real-time acquisition of climate data, ensures the timeliness and accuracy of the data, and avoids the lag of relying on long-term meteorological models.

[0059] More specifically, the climatic characteristics of nearby dates are extracted through historical climate data analysis and applied to the illumination data to extract climatic influencing factors. Based on the historical climate data of nearby dates, climate-related characteristics are extracted, such as: temperature: temperature affects the efficiency of solar panels. Too high or too low temperature will affect the power generation performance of the panels. Humidity: humidity may affect the cleanliness and efficiency of solar panels. Too high humidity may increase the attachment of pollutants. Precipitation: precipitation directly affects lighting conditions. On days with heavy precipitation, light is reduced. Wind speed: wind speed affects the surface temperature of the panels and improves power generation efficiency through convection heat dissipation. These climate characteristics are combined with the illumination data to extract specific climatic influencing characteristics, such as adjusting the temperature correction coefficient of the illumination data by temperature changes, and correcting the light intensity by humidity and precipitation.

[0060] More specifically, through precise extraction of climatic features, the impact of different climatic factors (such as temperature, humidity, precipitation, etc.) on illumination data can be effectively identified and quantified, thereby providing more accurate climate background data for the performance evaluation of solar panels, improving the accuracy of illumination data, and better reflecting the actual power generation capacity of solar panels under specific climatic conditions.

[0061] More specifically, the difference between the expected climate and the historical climate is analyzed, the possible changes in climate characteristics of the current date are inferred, and applied to the correction of climatic characteristics. The expected climate characteristics of the current date are compared with the historical climate characteristics of nearby dates. The main comparison items include: temperature difference: whether there is a large difference between the temperature of the current date and the historical temperature of nearby dates, humidity difference: whether the humidity increases or decreases, and whether it affects the efficiency of solar panels, precipitation difference: the difference between expected precipitation and historical precipitation, affecting the availability of light, wind speed difference: the change between expected wind speed and historical wind speed, affecting heat dissipation and solar panel efficiency. After comparison, the difference value is obtained, which indicates the degree of change between the expected climate and the historical climate, evaluates the impact of the difference relationship, and provides a basis for subsequent corrections.

[0062] More specifically, comparative analysis can accurately identify differences between climate characteristics, help analyze the extent to which current and historical climates affect light data, provide a quantitative analysis of the differences between predicted and historical climates, and help adjust current light data to make them more consistent with projected climate conditions.

[0063] More specifically, the climatic elements of adjacent dates are corrected through the difference relationship to make them more consistent with the climatic characteristics of the current date. Based on the difference relationship, the climatic characteristics that need to be adjusted are determined. For example, if the expected temperature is higher than the historical temperature, the light data needs to be temperature corrected, considering that high temperature may lead to reduced efficiency. If the expected precipitation is higher than the historical precipitation, the light intensity value needs to be reduced. The correction factor is applied to adjust the light data to ensure that the climatic elements of adjacent dates are closer to the current climatic characteristics. It is verified whether the corrected climatic elements are consistent with the expected climate characteristics to ensure the accuracy of the model.

[0064] More specifically, through correction, the illumination data can be dynamically adjusted according to the expected climate conditions to ensure that the data matches the actual climate conditions, thereby improving the adaptability and accuracy of the illumination data under different climate conditions, thereby making the performance prediction of solar panels more accurate.

[0065] More specifically, through the above steps, the climatic factors to which the solar panels are subjected on the current date are obtained, which provide a basis for power generation prediction and performance optimization. After comprehensive processing of historical climate data, expected climate data and difference correction, the climatic factors of the solar panels on the current date are obtained. These climatic factors (such as temperature, humidity, precipitation, etc.) are combined with the light data to generate the climate-adjusted light data for the current date.

[0066] More specifically, the resulting climatic factors can accurately reflect the working environment of solar panels under current climate conditions, help predict and optimize solar power generation capacity, and the corrected climatic data provides a reliable basis for the performance evaluation of solar panels and improves the operating efficiency of power generation systems under different climate conditions.

[0067] Preferably, the step of combining and analyzing the sunlight simulation model for the day with the light receiving performance model to obtain the initial light receiving characteristics of the solar panel for the day and the preset light receiving trajectory for the day includes: S24: combining the current day illumination simulation model with the light receiving performance model, so that the current day illumination simulation model and the light receiving performance model are in data connection state; S25: Based on the data connection state between the current-day illumination simulation model and the light receiving performance model, perform a time-series illumination environment simulation on the current-day illumination performance model according to the current-day illumination simulation model to obtain an illumination environment feature sequence that the environment in which the light receiving performance model is located will receive from morning to night on the current date; wherein the illumination environment feature sequence includes a plurality of illumination environment features arranged in chronological order, and the illumination environment feature is used to describe the illumination environment received by the solar cell panel corresponding to the illumination performance feature at a specified time; S26: applying each of the illumination environment features in the illumination environment feature sequence to the light receiving performance model in sequence, and performing light receiving performance effect evaluation at multiple inclination angles on the light receiving performance model to which the illumination environment features are applied, so as to obtain an inclination angle effect characteristic distribution of the light receiving performance model; wherein the inclination angle effect characteristic distribution is used to describe the light receiving performance effects of the solar cell panel at various inclination angles when corresponding to the illumination environment features; S27: performing connection selection processing on each of the inclination angle effect characteristic distributions according to the arrangement position of the illumination environment characteristic corresponding to each of the inclination angle effect characteristic distributions in the illumination environment characteristic sequence, so as to obtain a plurality of continuous inclination angle sequences; wherein the continuous inclination angle sequence comprises a plurality of inclination angle characteristics arranged in sequence according to a time series, and the inclination angle characteristic is the inclination angle of the solar cell panel corresponding to the illumination environment characteristic; S28: Analyzing the overall effect of each continuous inclination angle sequence and the sequence variation loss, so as to obtain the overall light receiving performance effect and the overall execution loss effect of each continuous inclination angle sequence; S29: interactively optimizing each of the continuous inclination angle sequences according to the overall light receiving performance effect and the overall execution loss effect of each of the continuous inclination angle sequences to obtain an optimal continuous inclination angle sequence; S210: extracting the initial inclination angle and the subsequent execution inclination angle of the optimal continuous inclination angle sequence to obtain the initial light receiving characteristics of the solar panel on the day and the preset light receiving trajectory on the day.

[0068] Specifically, the daily illumination simulation model is effectively combined with the light receiving performance model, and a data connectivity relationship is established to provide a basis for subsequent lighting environment simulation and light receiving effect analysis. The daily illumination simulation model is integrated with the light receiving performance model so that the two models can share data input and output. For example, the light intensity, light period, angle and other information output by the daily illumination simulation model can be passed as input to the light receiving performance model, which evaluates the actual light receiving performance of the solar panel based on these data, ensuring that the data formats and contents of the two can be seamlessly connected to avoid information loss or errors during data transmission. The illumination simulation and light receiving performance analysis are effectively integrated, providing an integrated technical means for dynamically simulating the light receiving characteristics of solar panels, realizing data sharing and transmission between models, and improving the response speed and accuracy of the entire system.

[0069] More specifically, the light environment of the light receiving performance model is simulated in time series through the daytime light simulation model to obtain a light environment feature sequence from morning to night. Based on the day's climate data, astronomical data (such as sun angle, cloud cover, time period, etc.) and the specific location of the solar panel, the light intensity, light angle and other information at each moment of the day are simulated, and the simulated light environment information is arranged in chronological order to form a time series. The data at each moment represents the specific light characteristics of the location of the solar panel. These characteristics include but are not limited to light intensity, radiation, sun angle, etc., and a detailed light environment feature sequence is obtained, which reflects the light changes in a complete day cycle, and provides accurate light environment data for subsequent light receiving performance evaluation, making the evaluation results closer to the actual situation.

[0070] More specifically, each lighting feature in the lighting environment feature sequence is applied to the light receiving performance model one by one, and the light receiving performance effect at different inclination angles is evaluated. Each lighting environment feature in the lighting environment feature sequence is applied to the light receiving performance model in turn. Each feature describes the lighting conditions at a specific moment, such as light intensity, sun angle, etc. Under each lighting feature, the light receiving performance model will be evaluated at different inclination angles (for example, different tilt angles and direction angles of solar panels). In this way, it is possible to understand how the light receiving performance of solar panels changes at different angles.

[0071] More specifically, by summarizing the light reception performance evaluation results at multiple inclination angles, the inclination angle effect characteristic distribution is generated to describe the light reception performance effects corresponding to various lighting environment characteristics. Through multi-angle analysis, the performance of solar panels at different inclination angles is evaluated, and the adaptability evaluation capability under different climatic conditions and changes in solar angle is improved. The generated inclination angle effect characteristic distribution provides a basis for optimizing the tilt angle of solar panels, which helps to improve their energy efficiency.

[0072] More specifically, according to the position and arrangement order of the distribution of the inclination angle effect characteristics, the light receiving performance of the solar panel is further adjusted and optimized. According to the position and arrangement order of the distribution of the inclination angle effect characteristics, it is analyzed which lighting environment characteristics have a greater impact on the light receiving performance of the solar panel and which angles perform better. Combined with the above analysis results, the light receiving performance of the solar panel is corrected. For example, the installation angle and orientation of the solar panel can be adjusted to improve energy efficiency, and dynamic optimization based on time-series illumination simulation and multi-angle evaluation is realized, providing the best light receiving angle and scheme for the solar panel, improving the ability of the solar panel to dynamically adjust according to environmental changes in actual applications, and maximizing its power generation efficiency.

[0073] Preferably, the step of analyzing the overall effect of each continuous inclination angle sequence and the sequence variation loss to obtain the overall light receiving performance effect and the overall execution loss effect of each continuous inclination angle sequence comprises: S281: taking each of the continuous inclination angle features in the continuous inclination angle sequence as an analysis unit, and performing effect analysis on each of the analysis units according to the distribution of inclination angle effect features corresponding to each of the analysis units, so as to obtain a direct parameter and a ranking parameter of the light receiving performance effect of each of the analysis units; S282: performing weighted analysis on the direct parameters and the sorting parameters of the light receiving performance effects of the respective analysis units to obtain light receiving performance evaluation values ​​of the respective analysis units, wherein the light receiving performance evaluation values ​​of the respective analysis units together constitute the overall light receiving performance effect of the continuous inclination angle sequence; S283: performing a multi-dimensional analysis of the execution loss on the inclination angle differences between the analysis units in the continuous inclination angle sequence, so as to obtain energy loss parameters and equipment wear parameters corresponding to the switching between the analysis units in the continuous inclination angle sequence; S284: Perform a weighted analysis on the energy loss parameters and equipment wear parameters corresponding to the switching between the analysis units to obtain the execution loss assessment amounts between the analysis units. The execution loss assessment amounts between the analysis units together constitute the overall execution loss effect of the continuous inclination angle sequence.

[0074] Specifically, the influence of each continuous inclination angle feature on the light receiving performance is analyzed, and its direct parameters and sorting parameters are extracted to evaluate the light receiving performance effect of each analysis unit. The inclination angle feature in each continuous inclination angle sequence is regarded as an analysis unit, and each analysis unit corresponds to a specific inclination angle (such as the tilt angle of a solar panel at a certain moment).

[0075] More specifically, for each analysis unit, the light receiving performance is analyzed using the inclination angle effect characteristic distribution corresponding to the unit. The inclination angle effect characteristic distribution generally includes indicators such as light intensity, energy conversion efficiency, and radiation reception at the angle.

[0076] More specifically, direct parameters and sorting parameters are extracted: direct parameters: such as light intensity, radiation, energy conversion efficiency, etc. under each analysis unit; sorting parameters: considering the relative ranking of the analysis unit with other analysis units, usually sorting based on lighting effects at different angles, and obtaining a ranking value that reflects the quality of light reception. By quantitatively evaluating the light reception performance of each analysis unit, we can fully understand the energy efficiency performance at various inclination angles. The combination of direct parameters and sorting parameters helps to more accurately evaluate the contribution and relative advantages and disadvantages of each unit under lighting conditions.

[0077] More specifically, the overall light receiving performance effect of the entire continuous inclination angle sequence is obtained by weighted analysis of the light receiving performance parameters of each analysis unit. Weighted analysis is performed according to certain weights based on the direct parameters and sorting parameters of each analysis unit. These weights can be dynamically allocated according to factors such as light intensity at different angles and energy conversion efficiency. The light receiving performance evaluation value of each analysis unit can be obtained in a weighted manner, which reflects the actual light receiving ability of the unit under specific conditions.

[0078] More specifically, the light receiving performance evaluation values ​​of all analysis units are summarized to obtain the overall light receiving performance effect of the entire continuous inclination angle sequence. This evaluation value integrates the lighting performance of each analysis unit in the entire sequence. The weighted analysis ensures that under different lighting conditions, those angles that contribute more to the overall light receiving performance are given priority. The overall light receiving performance effect obtained provides a global performance reference for subsequent optimization and helps select the optimal solar panel angle configuration.

[0079] More specifically, the energy loss and equipment wear caused by the angle switching between different analysis units are analyzed, the execution loss effect of the entire system is evaluated, and the inclination angle difference between each analysis unit and its adjacent units before and after is calculated. Different inclination angle differences may cause the adjustment and movement of the equipment, which in turn affects the energy loss and mechanical wear. When the inclination angle changes, the light receiving efficiency of the solar panel may drop instantaneously, resulting in a certain amount of energy loss. This loss can be calculated based on the angle difference. Frequent or drastic angle adjustments may cause wear on the mechanical parts of the panel (such as drive motors, brackets, etc.). Therefore, the greater the angle difference, the greater the equipment wear may be. Energy loss and equipment wear parameter calculation: For the angle difference between each analysis unit, calculate its corresponding energy loss and equipment wear parameters.

[0080] More specifically, through multi-dimensional analysis, the energy loss and equipment wear during the execution process are taken into account, avoiding the problem of only focusing on lighting effects and ignoring mechanical losses. A tool for comprehensively evaluating the solar panel angle adjustment strategy is provided, which helps to reduce unnecessary losses caused by frequent angle adjustments.

[0081] More specifically, the execution loss parameters are weighted and analyzed to obtain the overall execution loss effect in order to balance the trade-off between energy collection efficiency and equipment wear. The execution loss evaluation amount of each analysis unit is calculated using a weighted analysis method based on the energy loss and equipment wear caused by the angle switching between each analysis unit. The weighting can take into account the amplitude and frequency of the angle change and its impact on energy loss and wear. By summarizing the execution loss evaluation amounts between all analysis units, the overall execution loss effect of the entire continuous tilt angle sequence is obtained. This result reflects the comprehensive loss level of the system during the angle adjustment process.

[0082] More specifically, this step helps to minimize system losses while improving light receiving efficiency by considering the relationship between energy loss and equipment wear. The overall execution loss effect provides a basis for optimizing the angle adjustment strategy, which can find the best balance between performance and life.

[0083] Preferably, the steps of continuously recording the solar panel's conversion of light into electrical energy on the current date to obtain the solar panel's light reception characteristic sequence for the day, and performing trajectory correction on the preset light reception trajectory for the day according to the light reception characteristic sequence for the day, and controlling the solar panel's inclination angle according to the corrected preset light reception trajectory include: S31: continuously recording the light-converted electric energy of the solar panel on the current date to obtain the light-converted electric energy accumulated by the solar panel at each moment, and based on the light-converted electric energy accumulated by the solar panel at each moment, the light-receiving effect characteristics of the solar panel at each moment together constitute the light-receiving characteristic sequence of the solar panel on that day; S32: retrieving the theoretical light receiving performance effect calculated when the preset light receiving trajectory is preset based on the database, and performing numerical difference analysis between the light receiving effect characteristics and the theoretical light receiving performance effect to obtain a light receiving effect difference amount; S33: performing a traceability analysis of the difference factors of the light receiving effect difference amount according to a preset difference factor identification standard to obtain a possible difference factor corresponding to the light receiving effect difference amount; S34: retrieving theoretical lighting environment characteristics calculated when the preset light receiving trajectory is preset and planned based on the database, and performing environmental characteristic correction on the theoretical lighting environment characteristics based on the possible difference factor; S35: Correcting the preset light receiving trajectory according to the corrected lighting environment characteristics, so as to control the inclination angle of the solar cell panel according to the corrected preset light receiving trajectory.

[0084] Specifically, by continuously recording the solar panel's light-conversion electrical energy at each moment, we obtain an accurate light-receiving feature sequence, and then analyze its light-receiving effect. We monitor the solar panel's light-conversion electrical energy on the current date in real time. The solar panel's light-conversion electrical energy is a dynamic process, which is affected by factors such as weather changes, solar radiation intensity, and time. At each moment, the solar panel's light-conversion electrical energy is recorded and accumulated. These data reflect the light intensity and light energy conversion effect at each moment.

[0085] More specifically, based on the accumulated electric energy data at each moment, the light effect characteristics at that moment (such as light intensity, angle optimization effect, etc.) are evaluated, and the light effect characteristics at each moment are summarized to form a light feature sequence for the day. This sequence reflects the light conversion efficiency and actual light conditions of the panels in different time periods of the day. By recording and analyzing the light-to-electricity conversion of solar panels, high-precision light data is obtained, which provides a detailed foundation for subsequent trajectory correction and optimization. This step helps to capture the impact of solar radiation changes on panel performance in real time, making it easier to adjust the light trajectory and angle.

[0086] More specifically, by comparing and analyzing the theoretical effects with the preset light-receiving trajectory, the differences in the light-receiving effects are found, and then the trajectory is corrected. The theoretical light-receiving performance effect calculated based on environmental parameters (such as radiation intensity, climate change, etc.) when planning the preset light-receiving trajectory is obtained from the database. This theoretical effect represents the best light-receiving effect that the solar panel should achieve under ideal conditions.

[0087] More specifically, the actual measured light receiving effect characteristics are compared with the theoretically calculated light receiving performance effects, and the numerical difference between the two is calculated to obtain the light receiving effect difference. The difference can be quantified as the difference in light intensity, the deviation in conversion efficiency, etc. By comparing the actual light receiving effect with the theoretical effect, it is possible to accurately identify the time periods or angles at which the light receiving effect of the solar panel deviates, providing data support for further optimization. Difference analysis helps identify potential environmental changes or equipment problems, and provides a basis for subsequent corrective measures.

[0088] More specifically, by retrospectively analyzing the differences in lighting effects, possible causes or influencing factors are identified to guide subsequent trajectory corrections. According to preset difference factor identification standards (such as temperature changes, cloud density, air humidity and other factors), the differences in lighting effects are analyzed to trace the factors that may affect the lighting effects. By analyzing these difference factors, the reasons that may cause the difference between the lighting effects and theoretical expectations are found out. For example, low light intensity in certain periods may be due to changes in clouds; efficiency differences at certain angles may be due to light refraction or occlusion effects.

[0089] More specifically, based on the analysis results, the main factors affecting the light receiving effect are identified and their possible impact on the performance of the solar panels is evaluated. This step helps to find the real root cause of the deviation among multiple possible factors, avoid blind adjustments, and enhance the accuracy of the system. By identifying and analyzing the influencing factors, the potential impact of future weather changes on the light receiving effect can be predicted, so that adjustments can be made in advance.

[0090] More specifically, based on the identified difference factors, the lighting environment characteristics are corrected to more accurately reflect the actual lighting conditions. The theoretical lighting environment characteristics calculated when the preset light-receiving trajectory is planned are retrieved from the database, including parameters such as light intensity, radiation direction, and temperature. The theoretical lighting environment characteristics are corrected based on possible difference factors (such as actual cloud changes, temperature, humidity, etc.). For example, if it is found that the actual light intensity is low due to cloud changes in certain periods of time, the light intensity can be corrected according to the cloud prediction model. The corrected lighting environment characteristics can more realistically reflect the actual lighting conditions and avoid errors between the theoretical model and the actual situation. This correction mechanism improves the system's adaptability to environmental changes and makes the adjustment of the solar panels more in line with real-time lighting conditions.

[0091] More specifically, according to the corrected lighting environment characteristics, the original preset light receiving trajectory is adjusted to make the light receiving angle of the solar panel more consistent with the actual lighting conditions, and the light receiving trajectory is replanned according to the corrected lighting environment characteristics. The new trajectory takes into account the influence of real-time light intensity, environmental changes (such as cloud cover, weather changes, etc.) and other factors. According to the corrected trajectory, the inclination angle of the solar panel is adjusted to maximize the light received in each period.

[0092] More specifically, through precise trajectory correction, the inclination angle of the solar panel can be adjusted to be more in line with the actual lighting conditions, significantly improving the light conversion efficiency. This step provides flexibility and adaptability, allowing the panel to maintain the best light receiving state under different weather conditions.

[0093] Reference Figure 2 As shown, in a second aspect, the present invention provides an operation control system of a solar panel, which is used to implement an operation control method of a solar panel as described in any one of the first aspects, including: A digital simulation module, used to obtain the panel specification information and setting location information of the solar panel, and perform digital simulation analysis of the panel performance and the sunlight environment of the solar panel according to the panel specification information and the setting location information, so as to obtain a light receiving performance model and a sunlight environment model of the solar panel; A trajectory analysis module, used to assign seasonal elements and climatic elements of the current date to the daylight environment model according to the historical database, so as to obtain a daylight simulation model based on the daylight environment model, and combine the daylight simulation model with the light receiving performance model for analysis to obtain the initial light receiving characteristics of the solar panel on the current day and the preset light receiving trajectory of the current day; wherein the initial light receiving characteristics of the current day are used to describe the inclination angle of the solar panel initially receiving light on the current date, and the preset light receiving trajectory of the current day are used to describe the change in the inclination angle of the solar panel receiving light that is expected to be planned to change with time on the current date; The trajectory correction module is used to continuously record the light-conversion electrical energy of the solar panel on the current date to obtain the light-receiving characteristic sequence of the solar panel on the current day, and to perform trajectory correction on the preset light-receiving trajectory of the current day according to the light-receiving characteristic sequence of the current day, so as to control the inclination angle of the solar panel according to the corrected preset light-receiving trajectory.

[0094] In this embodiment, for the specific implementation of each module in the above system embodiment, please refer to the above method embodiment, which will not be repeated here.

[0095] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for controlling the operation of a solar panel, characterized in that: include: Acquiring panel specification information and setting location information of the solar panel, and performing digital simulation analysis of panel performance and the sunlight environment in which the solar panel is located on the solar panel according to the panel specification information and the setting location information, so as to obtain a light receiving performance model and a sunlight environment model of the solar panel; According to the historical database, the seasonal elements and climatic elements of the current date are assigned to the daylight environment model to obtain a daylight simulation model based on the daylight environment model, and the daylight simulation model is combined with the light receiving performance model and analyzed to obtain the initial light receiving characteristics of the solar panel on the current day and the preset light receiving trajectory on the current day; wherein the initial light receiving characteristics of the current day are used to describe the inclination angle of the solar panel initially receiving light on the current date, and the preset light receiving trajectory on the current day is used to describe the change in the inclination angle of the solar panel receiving light that is expected to be planned to change with time on the current date; The solar panel is continuously recorded for converting sunlight into electrical energy on the current date to obtain a characteristic sequence of light reception of the solar panel on the current day, and a trajectory correction is performed on the preset light reception trajectory on the current day according to the characteristic sequence of light reception on the current day, so as to control the inclination angle of the solar panel according to the corrected preset light reception trajectory.

2. The operation control method of the solar panel according to claim 1, characterized in that: The steps of obtaining the panel specification information and setting location information of the solar panel, and performing digital simulation analysis on the panel performance and the sunlight environment of the solar panel according to the panel specification information and the setting location information to obtain the light receiving performance model and the sunlight environment model of the solar panel include: Acquire the panel specification information of the solar panel; wherein the panel specification information includes the appearance specification information and the photoelectric conversion performance information of the solar panel; Performing digital simulation of the external structure of the solar panel according to the external shape specification information to obtain a simulation model of the light-receiving surface of the solar panel; According to the photoelectric conversion performance information, the performance parameters of the photoelectric conversion of the light-receiving surface simulation model are configured to obtain the light-receiving performance model; Acquire the setting and positioning information of the solar panel; wherein the setting and positioning information includes a description of the setting and positioning of the solar panel under multiple positioning standards, and the positioning standards include latitude and longitude standards, altitude standards, and landform environment standards; A multi-dimensional analysis is performed on the basic receiving environment of sunlight at the location of the solar panel according to the setting positioning information, and the influencing factors and influencing weights of the setting positioning description under each positioning standard on the sunlight environment of the solar panel are obtained through the multi-dimensional analysis; A digital simulation analysis is performed on the sunlight environment in which the solar panel is located according to various influencing factors and influencing weights to obtain a sunlight environment model of the solar panel.

3. The operation control method of the solar panel according to claim 1, characterized in that: The step of assigning seasonal elements and climatic elements of the current date to the daylight environment model according to the historical database to obtain a daylight simulation model based on the daylight environment model comprises: Acquire date information of the current date, and substitute the date information of the current date into a historical database to perform date positioning and historical data search, so as to obtain historical reference data of the current date; wherein the historical reference data includes ambient light data, seasonal characteristic data, and climate characteristic data of the solar panel on adjacent dates; Extracting the characteristics of seasonal and climatic influences from the ambient light data of the solar panel to obtain the seasonal and climatic factors to which the solar panel is subjected on the current date; The seasonal elements and climatic elements of the current date are assigned to the daylight environment model, and the daylight environment model is made to simulate the expected daylight environment of the current date according to the seasonal elements and climatic elements of the current date to obtain a daylight simulation model based on the daylight environment model.

4. The operation control method of the solar panel according to claim 3, characterized in that: The step of extracting the seasonal influence feature of the ambient light data of the solar panel to obtain the seasonal factors to which the solar panel is subjected on the current date comprises: Determine the seasonal characteristics corresponding to the ambient light data of the solar panel according to the date information of the current date, and schedule the seasonal impact identification standard corresponding to the seasonal characteristics; Extracting the characteristics of the influencing factors from the ambient light data of the solar panel according to the seasonal impact identification standard, so as to obtain the seasonal factors to which the solar panel is subjected on the adjacent dates; The difference relationship between the seasonal element of the solar panel on the current date and the seasonal element suffered by the solar panel on the adjacent date is analyzed according to the date information of the current date, and the difference correction processing is performed on the seasonal element suffered by the solar panel on the adjacent date according to the difference relationship obtained by the analysis, so as to obtain the seasonal element suffered by the solar panel on the current date.

5. The operation control method of the solar panel according to claim 3, characterized in that: The step of extracting the features of the climate impact on the ambient light data of the solar panel to obtain the climate elements to which the solar panel is subjected on the current date comprises: Obtain historical climate characteristics of nearby dates and predicted climate characteristics of the current date through network communication; Extracting the features of the climate impact on the ambient light data of the solar panel according to the historical climate characteristics of the adjacent dates, so as to obtain the climate factors to which the solar panel was subjected on the adjacent dates; The predicted climate characteristics are compared with the historical climate characteristics to obtain a difference relationship between the predicted climate characteristics and the historical climate characteristics to which the solar panel is subjected on a current date, and climate elements to which the solar panel is subjected on adjacent dates are corrected according to the difference relationship to obtain the climate elements to which the solar panel is subjected on the current date.

6. The operation control method of the solar panel according to claim 1, characterized in that: The steps of combining and analyzing the sunlight simulation model of the day with the light receiving performance model to obtain the initial light receiving characteristics of the solar panel of the day and the preset light receiving trajectory of the day include: Combining the current day illumination simulation model with the light receiving performance model so that the current day illumination simulation model and the light receiving performance model are in a data connection state; Based on the data connection state between the current day illumination simulation model and the light receiving performance model, the current day illumination environment of the light receiving performance model is simulated in time sequence according to the current day illumination simulation model, so as to obtain a light environment feature sequence that the environment where the light receiving performance model is located will receive from morning to night on the current date; wherein the light environment feature sequence includes a plurality of light environment features arranged in chronological order, and the light environment feature is used to describe the light environment received by the solar cell panel corresponding to the light receiving performance feature at a specified time; According to each of the illumination environment characteristics in the illumination environment characteristic sequence, the illumination performance model is sequentially applied, and the illumination performance effect of multiple inclination angles is evaluated on the illumination performance model to which the illumination environment characteristics are applied, so as to obtain an inclination angle effect characteristic distribution of the illumination performance model; wherein the inclination angle effect characteristic distribution is used to describe the illumination performance effect of the solar cell panel at various inclination angles when corresponding to the illumination environment characteristics; According to the arrangement position of the illumination environment characteristics corresponding to each of the inclination angle effect characteristic distributions in the illumination environment characteristic sequence, each of the inclination angle effect characteristic distributions is subjected to connection selection processing to obtain a plurality of continuous inclination angle sequences; wherein the continuous inclination angle sequence comprises a plurality of inclination angle characteristics arranged in sequence according to a time series, and the inclination angle characteristic is the inclination angle of the solar cell panel when it corresponds to the illumination environment characteristic; Analyzing the overall effect of each continuous inclination angle sequence and the sequence variation loss to obtain the overall light receiving performance effect and the overall execution loss effect of each continuous inclination angle sequence; Interactively optimizing each of the continuous inclination angle sequences according to the overall light receiving performance effect and the overall execution loss effect of each of the continuous inclination angle sequences to obtain an optimal continuous inclination angle sequence; The initial inclination angle and the subsequent execution inclination angle of the optimal continuous inclination angle sequence are extracted to obtain the initial light receiving characteristics of the solar panel on the day and the preset light receiving trajectory on the day.

7. The operation control method of the solar panel according to claim 6, characterized in that: The steps of analyzing the overall effect of each continuous inclination angle sequence and the sequence variation loss to obtain the overall light receiving performance effect and the overall execution loss effect of each continuous inclination angle sequence include: Each of the continuous inclination angle features in the continuous inclination angle sequence is used as an analysis unit, and the effect analysis is performed on each analysis unit according to the distribution of the inclination angle effect characteristics corresponding to each analysis unit, so as to obtain a direct parameter and a ranking parameter of the light receiving performance effect of each analysis unit; A weighted analysis is performed on the direct parameters and the sorting parameters of the light receiving performance effect of each of the analysis units to obtain a light receiving performance evaluation value of each of the analysis units, and the light receiving performance evaluation values ​​of each of the analysis units together constitute the overall light receiving performance effect of the continuous inclination angle sequence; Performing a multi-dimensional analysis of the execution loss on the inclination angle differences between the analysis units in the continuous inclination angle sequence to obtain energy loss parameters and equipment wear parameters corresponding to the switching between the analysis units in the continuous inclination angle sequence; A weighted analysis is performed on the energy loss parameters and equipment wear parameters corresponding to the switching between the analysis units to obtain the execution loss assessment amounts between the analysis units. The execution loss assessment amounts between the analysis units together constitute the overall execution loss effect of the continuous inclination angle sequence.

8. The operation control method of the solar panel according to claim 6, characterized in that: The steps of continuously recording the solar panel's conversion of light into electrical energy on the current date to obtain the solar panel's light reception characteristic sequence for the day, and performing trajectory correction on the preset light reception trajectory for the day according to the light reception characteristic sequence for the day, and controlling the solar panel's inclination angle according to the corrected preset light reception trajectory include: Continuously recording the light-converted electric energy of the solar panel on the current date to obtain the light-converted electric energy accumulated by the solar panel at each moment, analyzing the light-receiving effect characteristics of the solar panel at each moment based on the light-converted electric energy accumulated by the solar panel at each moment, the light-receiving effect characteristics of the solar panel at each moment together forming a light-receiving characteristic sequence of the solar panel on that day; Retrieving the theoretical light receiving performance effect calculated when the preset light receiving trajectory is preset and performing a numerical difference analysis between the light receiving effect characteristics and the theoretical light receiving performance effect to obtain a light receiving effect difference amount; Performing a traceability analysis of the difference factors of the light receiving effect difference amount according to a preset difference factor identification standard to obtain a possible difference factor corresponding to the light receiving effect difference amount; Retrieving theoretical lighting environment characteristics calculated when the preset light receiving trajectory is preset based on the database, and performing environmental characteristic correction on the theoretical lighting environment characteristics based on the possible difference factors; The preset light receiving trajectory is corrected according to the corrected lighting environment characteristics, so as to control the inclination angle of the solar cell panel according to the corrected preset light receiving trajectory.

9. A solar panel operation control system, characterized in that: A method for controlling the operation of a solar panel according to any one of claims 1 to 8, comprising: A digital simulation module, used to obtain the panel specification information and setting location information of the solar panel, and perform digital simulation analysis of the panel performance and the sunlight environment of the solar panel according to the panel specification information and the setting location information, so as to obtain a light receiving performance model and a sunlight environment model of the solar panel; A trajectory analysis module, used to assign seasonal elements and climatic elements of the current date to the daylight environment model according to the historical database, so as to obtain a daylight simulation model based on the daylight environment model, and combine the daylight simulation model with the light receiving performance model for analysis to obtain the initial light receiving characteristics of the solar panel on the current day and the preset light receiving trajectory of the current day; wherein the initial light receiving characteristics of the current day are used to describe the inclination angle of the solar panel initially receiving light on the current date, and the preset light receiving trajectory of the current day are used to describe the change in the inclination angle of the solar panel receiving light that is expected to be planned to change with time on the current date; The trajectory correction module is used to continuously record the light-conversion electrical energy of the solar panel on the current date to obtain the light-receiving characteristic sequence of the solar panel on the current day, and to perform trajectory correction on the preset light-receiving trajectory of the current day according to the light-receiving characteristic sequence of the current day, so as to control the inclination angle of the solar panel according to the corrected preset light-receiving trajectory.

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