Efficient solar power generation panel lighting angle optimization method based on intelligent tracking algorithm

Abstract

The invention provides a high-efficiency solar power generation panel lighting angle optimization method based on an intelligent tracking algorithm, and belongs to the technical field of sun tracking. The method comprises the following steps: predicting the elevation angle and azimuth angle of the sun every day according to astronomical data, constructing a sun prediction model, and predicting the sun path in a plurality of hours in the future; the semispherical precise sun position recognition device is arranged to precisely recognize the position of the sun, the solar panel is controlled and adjusted, and the position of the solar panel is adjusted according to the recognized precise position of the sun after the time is fixed. The position of the sun is predicted through astronomical data, then a path is predicted through a prediction model, finally the position of the sun is accurately recognized through a hemispherical recognition device, accurate detection of the position of the sun is achieved, and meanwhile the solar panel can receive solar energy to the maximum extent from rough control to fine adjustment. And the maximum generating capacity is realized.

Description

Technical Field

[0001] The present invention relates to the field of solar tracking technology, and in particular to a method for optimizing the lighting angle of a high-efficiency solar power generation panel based on an intelligent tracking algorithm. Background Art

[0002] As the global demand for clean energy grows, solar energy as a renewable resource has received widespread attention. However, traditional fixed solar panels cannot adjust their angles as the sun's position changes, resulting in them not receiving the maximum amount of sunlight for most of the day, which affects the energy conversion efficiency. In order to overcome this limitation, a variety of automatic tracking systems have been proposed, but existing technologies often have problems such as high cost, complex structure or slow response speed.

[0003] Existing solar tracking basically relies on a single detection information or algorithm to track the sun, so that the power generation of solar panels can reach the optimal value. However, due to the changeable weather, the single information detection is often rough and cannot be accurately tracked. Therefore, it is necessary to design an efficient solar panel lighting angle optimization method based on an intelligent tracking algorithm. Summary of the invention

[0004] The purpose of the present invention is to provide a method for optimizing the lighting angle of a solar panel based on an intelligent tracking algorithm to solve the technical problem of inaccuracy of existing solar tracking methods.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is as follows:

[0006] A method for optimizing the lighting angle of a high-efficiency solar panel based on an intelligent tracking algorithm, the method comprising the following steps:

[0007] Step 1: Predict the altitude and azimuth of the sun every day based on astronomical formulas and date data;

[0008] Step 2: Build a solar prediction model to predict the path of the sun in the next few hours based on historical meteorological data, future weather forecast data, and the sun's trajectory;

[0009] Step 3: Setting a hemispherical sun precise position recognition device to accurately recognize the sun's position;

[0010] Step 4: When adjusting the position of the solar panels, make an initial adjustment at the beginning of the day based on the altitude and azimuth of the solar energy each day, and then adjust it based on the path of the sun in the next few hours;

[0011] Step 5: After a fixed time, adjust the position of the solar panel according to the precise position of the sun.

[0012] Furthermore, the process of determining the altitude angle and azimuth angle of the sun in step 1 is:

[0013] The solar altitude angle h is: h = arcsin (sinδ·sinφ+cosδ·cosφ·cosH), where h is the solar altitude angle, δ is the solar declination, φ is the geographical latitude of the observation point, and H is the solar hour angle;

[0014] The azimuth angle A of the sun is: A = arctan2(-sinH, tanδ·cosφ-sinφ·cosH), the return value range of the arctan2 function is -π to π, for the sun's declination δ and hour angle H, it determines the declination δ and hour angle H according to the current date and time and the longitude and latitude of the location, the declination δ is: δ = arcsin(0.39785·sin(0.98565·(N-79.346)+1.914·sin(0.98565·(N-79.346)))), N represents the day of the year, starting from January 1, and the hour angle is obtained by subtracting noon time from the local time, and changes by about 15 degrees every hour.

[0015] Furthermore, the specific process of step 2 is as follows: historical meteorological data and future weather forecast data are obtained from the official meteorological data service of the China Meteorological Administration website, data points that are obviously deviated from the normal range are identified and removed, missing data records are filled by interpolation method to ensure data integrity, numerical features are scaled so that all input variables are within a similar order of magnitude, year, month and day of the week information is extracted from the timestamp as features, new features are constructed based on the weather conditions in the past several hours or days to help capture long-term trends, geographic locations are converted into coordinate form, and the influence of terrain height factors is considered. The information of sunrise and sunset time and solar altitude angle obtained by astronomical calculations is used as part of the input features, and the long short-term memory network LSTM is selected, and then the training data is input into the long short-term memory network LSTM for training. During training, the best parameter combination is found through grid search, and the model performance is evaluated through K-fold cross validation. Then, weather forecast data for the next several hours is input into the trained model, and then the sun path for the next several hours is output.

[0016] Furthermore, in step 3, the hemispherical sun precise position identification device includes a support rod, a hemisphere and several directional solar intensity sensors, the hemisphere is arranged on the support rod, the several directional solar intensity sensors are arranged on the hemisphere, and the end of each directional solar intensity sensor is tilted to point to the center of the hemisphere, and then when the sun shines on the hemispherical sun precise position identification device, the solar intensity data of all the directional solar intensity sensors are detected, and the position pointed to by the strongest one or several directional solar intensity sensors is the most precise position of the sun, and the hemispherical sun precise position identification device is arranged on the side of the solar panel, and the height of the support rod is consistent with the height of the support plate of the solar panel.

[0017] Furthermore, the top of the directional solar intensity sensor is set to a hemispherical structure, and the hemispherical structure is coated with a sunlight sensing coating. Several directional solar intensity sensors are arranged in contact with each other on a hemispherical surface. When the sun is directly shining on the top of the hemisphere of the directional solar intensity sensor, the sensing intensity of the directional solar intensity sensor is the largest. If it is detected that the values ​​of the solar intensity sensed by more than one directional solar intensity sensor are the same and are the maximum values, the pointing angle of each directional solar intensity sensor with the maximum value is identified. If the directional solar intensity sensors with the maximum values ​​are not adjacent to each other, the pointing directions of all the directional solar intensity sensors with the maximum values ​​are averaged. When there are more than or equal to two solar intensity sensors with the largest sensing values ​​that are adjacent to each other, and the other solar intensity sensors with the maximum values ​​are not adjacent to each other, the solar intensity sensors with the maximum sensing values ​​that are not adjacent to each other are discarded.

[0018] Furthermore, a semicircular brush is provided on the hemispherical sun precise position identification device to periodically clean the hemispherical sun precise position identification device to prevent dust from affecting the detection.

[0019] Furthermore, in step 4, when controlling the solar panels, the daytime of a day is used as a unit. Before the sun comes out, the movement trajectory is preliminarily planned according to the detection in step 1. At the same time, the solar panels are rotated to the initial position of the movement trajectory before the sun comes out. Then, after obtaining the weather forecast data, the solar prediction model is used to predict the path of the sun in the next few hours, and then the solar panels are controlled to rotate to the initial position of the sun's path.

[0020] Furthermore, in step 5, the hemispherical sun precise position recognition device senses the precise direction of the sun in real time, and then controls the solar panels to face the sun at intervals of 5-10 minutes, and achieves maximum power generation through first rough control of the solar panels, then path control, and then precise adjustment control.

[0021] The present invention has the following beneficial effects due to the adoption of the above technical solution:

[0022] The present invention first predicts the position of the sun through astronomical data, then predicts the path through a prediction model, and finally accurately identifies the position of the sun through a hemispherical recognition device, thereby achieving accurate detection of the sun's position. At the same time, from rough control to fine adjustment, the solar panels can receive the maximum amount of solar energy and achieve maximum power generation. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 is a flow chart of the method of the present invention;

[0024] Figure 2 It is a schematic diagram of the hemispherical sun precise position structure of the present invention;

[0025] In the attached drawings, 1-support rod, 2-hemispherical body, 3-directional solar intensity sensor. DETAILED DESCRIPTION

[0026] 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 with reference to the accompanying drawings and preferred embodiments. However, it should be noted that many details listed in the specification are only for the purpose of enabling the reader to have a thorough understanding of one or more aspects of the present invention, and these aspects of the present invention can be implemented even without these specific details.

[0027] like Figure 1 As shown, a method for optimizing the lighting angle of a high-efficiency solar panel based on an intelligent tracking algorithm comprises the following steps:

[0028] Step 1: Predict the altitude and azimuth of the sun every day based on astronomical formulas and date data. The process of determining the altitude and azimuth of the sun is as follows:

[0029] The solar altitude angle h is: h = arcsin (sinδ·sinφ+cosδ·cosφ·cosH), where h is the solar altitude angle, δ is the solar declination, φ is the geographical latitude of the observation point, and H is the solar hour angle;

[0030] The azimuth angle A of the sun is: A = arctan2(-sinH, tanδ·cosφ-sinφ·cosH), the return value range of the arctan2 function is -π to π, for the sun's declination δ and hour angle H, it determines the declination δ and hour angle H according to the current date and time and the longitude and latitude of the location, the declination δ is: δ = arcsin(0.39785·sin(0.98565·(N-79.346)+1.914·sin(0.98565·(N-79.346)))), N represents the day of the year, starting from January 1, and the hour angle is obtained by subtracting noon time from the local time, and changes by about 15 degrees every hour.

[0031] Step 2: Build a solar prediction model to predict the path of the sun in the next few hours based on historical meteorological data, future weather forecast data and solar trajectory. Both historical meteorological data and future weather forecast data are obtained from the official meteorological data service on the website of the China Meteorological Administration. Identify and remove data points that are obviously deviated from the normal range, use interpolation to fill missing data records to ensure data integrity, scale numerical features so that all input variables are in a similar order of magnitude, extract year, month and day of the week information from timestamps as features, construct new features based on weather conditions in the past few hours or days to help capture long-term trends, convert geographic locations into coordinate form, and consider the influence of terrain height factors. According to the information of sunrise and sunset time and solar altitude angle obtained by astronomical calculations, use it as part of the input features, select the long short-term memory network LSTM, and then input the training data into the long short-term memory network LSTM for training. During training, grid search is used to find the best parameter combination, and the model performance is evaluated through K-fold cross validation. Then, weather forecast data for the next few hours is input into the trained model, and then the path of the sun in the next few hours is output.

[0032] Step 3: Set up a hemispherical solar precise position identification device to accurately identify the position of the sun. The hemispherical solar precise position identification device includes a support rod 1, a hemispherical body 2 and a plurality of directional solar intensity sensors 3. The hemispherical body 2 is set on the support rod 1, and a plurality of directional solar intensity sensors 3 are set on the hemispherical body 2, and the end of each directional solar intensity sensor 3 is tilted to point to the center of the hemispherical body 2. Then, when the sun shines on the hemispherical solar precise position identification device, the solar intensity data of all directional solar intensity sensors 3 are detected, and the position pointed to by the strongest one or several directional solar intensity sensors 3 is the most accurate position of the sun. The hemispherical solar precise position identification device is set on the side of the solar power generation panel, and the height of the support rod 1 is consistent with the height of the support plate of the solar power generation panel.

[0033] The top of the directional solar intensity sensor 3 is set to a hemispherical structure, and the hemispherical structure is coated with a sunlight sensing coating. The coating converts light into an electrical signal. The larger the electrical signal, the stronger the light. Several directional solar intensity sensors 3 are arranged in a hemispherical surface in contact with each other. When the sun is directly shining on the top of the hemisphere of the directional solar intensity sensor 3, the sensing intensity of the directional solar intensity sensor 3 is the largest. If it is detected that the values ​​of the solar intensity sensed by more than one directional solar intensity sensor 3 are the same and are the maximum values, the pointing angle of each directional solar intensity sensor 3 with the maximum value is identified. If the directional solar intensity sensors 3 with the maximum values ​​are not adjacent to each other, the pointing directions of all the directional solar intensity sensors 3 with the maximum values ​​are averaged. When there are more than or equal to two solar intensity sensors 3 with the largest sensing values ​​that are adjacent to each other, and the other solar intensity sensors 3 with the maximum values ​​are not adjacent to each other, the solar intensity sensors 3 with the maximum sensing values ​​that are not adjacent to each other are discarded.

[0034] Each directional solar intensity sensor 3 is numbered, and a mapping table is set up. The number and the corresponding tilt angle are fixed as a whole, so the tilt angle of each directional solar intensity sensor 3 is also fixed, so as to achieve better detection of the direction of the sun. That is, when the sun is facing the directional solar intensity sensor 3, the received solar intensity is the largest. At this time, the tilt direction of the directional solar intensity sensor 3 is very necessary to control the position of the solar panel. A semicircular brush is set on the hemispherical solar precise position identification device, and the hemispherical solar precise position identification device is cleaned regularly to prevent dust from affecting the detection.

[0035] Step 4: When adjusting the position of the solar panel, at the beginning of the day, make an initial adjustment based on the altitude and azimuth of the solar energy every day, and then adjust it based on the path of the sun in the next few hours. When controlling the solar panel, take the daytime of the day as a unit. Before the sun comes out, first make a preliminary plan of the movement trajectory based on the detection in step 1. At the same time, rotate the solar panel to the initial position of the movement trajectory before the sun comes out. Then, after obtaining the weather forecast data, use the solar prediction model to predict the path of the sun in the next few hours, and then control the solar panel to rotate to the initial position of the sun's path.

[0036] Step 5: After a fixed time, adjust the position of the solar panel according to the precise position of the sun. The hemispherical sun precise position recognition device senses the precise direction of the sun in real time, and then controls the solar panel to face the sun at intervals of 5-10 minutes. The solar panel is roughly controlled first, then path controlled, and then precisely adjusted to achieve maximum power generation.

[0037] The position of the sun is predicted through astronomical data, and then the path is predicted through the prediction model. Finally, the position of the sun is accurately identified through the hemispherical recognition device to achieve accurate detection of the sun's position. At the same time, from rough control to fine adjustment, the solar panels can receive the maximum amount of solar energy and achieve the maximum power generation. Gradual control and optimization are achieved to avoid large-scale control after the sun comes out, which affects the power generation of the solar panels.

[0038] Matters not covered by the present invention are known technologies.

[0039] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A high-efficiency solar panel lighting angle optimization method based on intelligent tracking algorithm, characterized by: The method comprises the following steps: Step 1: Predict the altitude and azimuth of the sun every day based on astronomical formulas and date data; Step 2: Build a solar prediction model to predict the path of the sun in the next few hours based on historical meteorological data, future weather forecast data, and the sun's trajectory; Step 3: Setting a hemispherical sun precise position recognition device to accurately recognize the sun's position; Step 4: When adjusting the position of the solar panels, make an initial adjustment at the beginning of the day based on the altitude and azimuth of the solar energy each day, and then adjust it based on the path of the sun in the next few hours; Step 5: After a fixed time, adjust the position of the solar panel according to the precise position of the sun.

2. According to claim 1, a high-efficiency solar panel lighting angle optimization method based on intelligent tracking algorithm is characterized in that: The process of determining the solar altitude angle and azimuth angle in step 1 is as follows: the solar altitude angle h is: h = arcsin (sinδ·sinφ+cosδ·cosφ·cosH), where h is the solar altitude angle, δ is the solar declination, φ is the geographical latitude of the observation point, and H is the solar hour angle; The azimuth angle A of the sun is: A = arctan2(-sinH, tanδ·cosφ-sinφ·cosH), the return value range of the arctan2 function is -π to π, for the sun's declination δ and hour angle H, it determines the declination δ and hour angle H according to the current date and time and the longitude and latitude of the location, the declination δ is: δ = arcsin(0.39785·sin(0.98565·(N-79.346)+1.914·sin(0.98565·(N-79.346)))), N represents the day of the year, starting from January 1, and the hour angle is obtained by subtracting noon time from the local time, and changes by about 15 degrees every hour.

3. The method for optimizing the lighting angle of a high-efficiency solar panel based on an intelligent tracking algorithm according to claim 1, characterized in that: The specific process of step 2 is as follows: historical meteorological data and future weather forecast data are obtained from the official meteorological data service of the China Meteorological Administration website. Data points that are obviously deviated from the normal range are identified and removed. Missing data records are filled by interpolation to ensure data integrity. Numerical features are scaled so that all input variables are in a similar order of magnitude. Year, month and day of the week information is extracted from the timestamp as features. New features are constructed based on the weather conditions in the past few hours or days to help capture long-term trends. Geographic locations are converted into coordinate form, and the influence of terrain height factors is considered. The information on sunrise and sunset times and solar altitude angles obtained from astronomical calculations is used as part of the input features. The long short-term memory network LSTM is selected, and then the training data is input into the long short-term memory network LSTM for training. During training, the best parameter combination is found through grid search, and the model performance is evaluated through K-fold cross validation. Then, weather forecast data for the next few hours is input into the trained model, and the sun path for the next few hours is output.

4. The method for optimizing the lighting angle of a high-efficiency solar panel based on an intelligent tracking algorithm according to claim 1, characterized in that: In step 3, the hemispherical solar precise position identification device comprises a support rod (1), a hemispherical body (2) and a plurality of directional solar intensity sensors (3), wherein the hemispherical body (2) is arranged on the support rod (1), and the plurality of directional solar intensity sensors (3) are arranged on the hemispherical body (2), and the end of each directional solar intensity sensor (3) is tilted to point to the center of the hemispherical body (2), and then when the sun shines on the hemispherical solar precise position identification device, the solar intensity data of all directional solar intensity sensors (3) are detected, and the position pointed to by the strongest one or several directional solar intensity sensors (3) is the most precise position of the sun, and the hemispherical solar precise position identification device is arranged on the side of the solar power generation panel, and the height of the support rod (1) is consistent with the height of the support plate of the solar power generation panel.

5. The method for optimizing the lighting angle of a high-efficiency solar panel based on an intelligent tracking algorithm according to claim 4 is characterized in that: The top of the directional solar intensity sensor (3) is set as a hemispherical structure, and the hemispherical structure is coated with a sunlight sensing coating. A plurality of directional solar intensity sensors (3) are arranged in a hemispherical surface in a close relationship. When the sun shines directly on the top of the hemisphere of the directional solar intensity sensor (3), the sensing intensity of the directional solar intensity sensor (3) is the maximum. If it is detected that the values ​​of the solar intensities sensed by more than a dozen directional solar intensity sensors (3) are the same and are the maximum values, the pointing angle of each directional solar intensity sensor (3) with the maximum value is identified. If the directional solar intensity sensors (3) with the maximum values ​​are not adjacent to each other, the pointing directions of all the directional solar intensity sensors (3) with the maximum values ​​are averaged. When there are more than or equal to two solar intensity sensors (3) with the maximum sensing values ​​that are adjacent to each other, and the other solar intensity sensors (3) with the maximum values ​​are not adjacent to each other, the solar intensity sensors (3) with the maximum sensing values ​​that are not adjacent to each other are discarded.

6. The method for optimizing the lighting angle of a high-efficiency solar panel based on an intelligent tracking algorithm according to claim 4 is characterized in that: A semicircular brush is provided on the hemispherical sun precise position identification device, and the hemispherical sun precise position identification device is cleaned regularly to prevent dust from affecting detection.

7. The method for optimizing the lighting angle of a high-efficiency solar panel based on an intelligent tracking algorithm according to claim 1, characterized in that: In step 4, when controlling the solar panels, the daytime of a day is used as a unit. Before the sun comes out, the movement trajectory is preliminarily planned according to the detection in step 1. At the same time, the solar panels are rotated to the initial position of the movement trajectory before the sun comes out. Then, after obtaining the weather forecast data, the solar prediction model is used to predict the path of the sun in the next few hours, and then the solar panels are controlled to rotate to the initial position of the sun's path.

8. The method for optimizing the lighting angle of a high-efficiency solar panel based on an intelligent tracking algorithm according to claim 1, characterized in that: In step 5, the hemispherical sun precise position recognition device senses the precise direction of the sun in real time, and then controls the solar panels to face the sun at intervals of 5-10 minutes. The maximum power generation is achieved through the first rough control of the solar panels, then path control, and then precise adjustment control.

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