Photovoltaic system tracking method based on astronomical tracking algorithm

Abstract

The invention provides a photovoltaic system tracking method based on an astronomical tracking algorithm. The method comprises the following steps: acquiring historical environment data and real-time environment data; respectively calculating illumination quality scores according to the historical environment data and the real-time environment data, and taking the percentage of the ratio of the illumination quality score of the current environment data to the illumination quality score of the historical environment data as a standard for dividing weather types; according to an astronomical algorithm, respectively calculating the solar altitude and the solar azimuth at the current moment and the next moment, and generating a solar motion track through the solar altitude and the solar azimuth; and selecting different photovoltaic module tracking modes according to different weather types. According to the method, different tracking modes are implemented on the photovoltaic system according to different weather types, and the tracking angle is adjusted in real time according to actual conditions during tracking, so that the power generation efficiency of the photovoltaic system is improved.

Description

Technical Field

[0001] The invention relates to the technical field of photovoltaic power generation, and in particular to a photovoltaic system tracking method based on an astronomical tracking algorithm. Background Art

[0002] Photovoltaic tracking system is a photovoltaic system that can automatically track the sun and increase the overall power generation. At present, photovoltaic tracking system usually tracks the sun at an angle calculated by astronomical algorithms. Sun tracking is to calculate the solar altitude angle and solar azimuth angle based on geographic information and time, and then obtain the projection angle of the sun's rays on the plane perpendicular to the axis, and use the projection angle as the optimal tracking angle of the photovoltaic module.

[0003] However, different weather conditions such as cloudy, overcast, and sunny direct light, scattered light, and surface emissivity have a significant impact on the power generation of the photovoltaic tracking system, and the heat generated by the absorption of light will also affect the power generation efficiency of the photovoltaic tracking system. Therefore, it is very necessary to design a photovoltaic system tracking method based on astronomical tracking algorithms. Summary of the invention

[0004] The purpose of the present invention is to provide a photovoltaic system tracking method based on an astronomical tracking algorithm, implement different tracking modes according to different weather types, and make real-time adjustments to the tracking angle according to actual conditions during tracking to improve the power generation efficiency of the photovoltaic system.

[0005] To achieve the above object, the present invention provides the following solutions:

[0006] A photovoltaic system tracking method based on an astronomical tracking algorithm comprises the following steps:

[0007] Obtain historical and real-time environmental data;

[0008] The light quality scores are calculated according to the historical environment data and the real-time environment data, and the percentage of the light quality score of the current environment data to the light quality score of the historical environment data is used as the standard for dividing the weather types; the weather types include: sunny weather, cloudy weather and overcast weather;

[0009] Calculate the solar altitude angle and solar azimuth at the current moment and the next moment respectively according to the astronomical algorithm, and generate the solar motion trajectory through the solar altitude angle and solar azimuth;

[0010] Select different PV module tracking methods according to different weather types; tracking methods include: no tracking, tracking according to the sun's motion trajectory, and tracking according to the PV module status and the sun's motion trajectory.

[0011] Optionally, the calculation formula for the lighting quality score of the current environment data is: Among them, S1 is the light quality score of the current environmental data, k is the air quality, T is the air temperature, H is the air humidity, L is the light intensity, C is the total cloud cover, Q is the air clarity, V is the air visibility, α, β, γ, δ, ε and ∈ are all weight coefficients;

[0012] The calculation formula for the lighting quality score of historical environmental data is: Among them, S2 is the lighting quality score of historical environmental data, k i is the air quality of the ith historical environmental data, T i is the air temperature of the ith historical environmental data, H i is the air humidity of the ith historical environmental data, L i is the light intensity of the i-th historical environmental data, C i is the total cloud cover of the i-th historical environmental data, Q i is the air clarity of the i-th historical environmental data, V i is the air visibility of the i-th historical environmental data, and n is the number of historical environmental data.

[0013] Optionally, the percentage of the ratio of the illumination quality score of the current environment data to the illumination quality score of the historical environment data is used as a standard for classifying weather types. The specific steps include:

[0014] When the percentage is less than 35 percent, the current weather is judged as cloudy;

[0015] When the percentage is greater than or equal to 35 percent and less than 70 percent, the current weather is judged as cloudy;

[0016] When the percentage is greater than or equal to seventy percent, the current weather is judged to be sunny.

[0017] Optionally, different photovoltaic module tracking methods are selected according to different weather types. The specific steps include:

[0018] When the weather type is cloudy, the tracking mode of the PV modules is no tracking;

[0019] When the weather type is cloudy, the photovoltaic module is tracked according to the movement of the sun;

[0020] When the weather type is sunny, the tracking method of the photovoltaic modules is to track according to the status of the photovoltaic modules and the movement trajectory of the sun.

[0021] Optionally, when the weather type is cloudy, the tracking mode of the photovoltaic component is no tracking, and the specific steps are: when the weather type is cloudy, the photovoltaic component does not rotate, and the tracking angle of the photovoltaic component is fixed at 30°.

[0022] Optionally, when the weather type is cloudy, the tracking method of the photovoltaic module is to track according to the sun's movement trajectory. The specific steps are: when the weather type is cloudy, the current tracking angle of the photovoltaic module remains perpendicular to the incident angle of sunlight, the sun's position at the next moment is predicted by the sun's movement trajectory, and the current tracking angle is adjusted according to the sun's position at the next moment; when the sun sets, the photovoltaic module is adjusted to the tracking method of cloudy weather.

[0023] Optionally, when the weather type is sunny, the photovoltaic module is tracked according to the photovoltaic module state and the sun's motion trajectory, and the specific steps include:

[0024] Calculate the real-time radiation incident angle according to the real-time solar radiation intensity collected by the photovoltaic module;

[0025] Calculate the shading ratio based on the real-time power changes of the photovoltaic modules;

[0026] The adjustment index is calculated according to the real-time radiation incident angle, shielding ratio, temperature of the photovoltaic module, wind speed and direction, and air temperature, and the tracking angle in cloudy weather is adjusted according to the adjustment index to obtain the tracking angle in sunny weather.

[0027] Optionally, the calculation formula for the horizontal angle of the real-time radiation incident angle is: Where θ is the horizontal angle, is the y-axis weighted partial derivative of solar radiation, is the weighted partial derivative of the x-axis of solar radiation; the calculation formula of the weighted partial derivative of the y-axis of solar radiation is: The calculation formula of the x-axis weighted partial derivative of solar radiation is: Where n is the number of collection points for collecting real-time solar radiation intensity, I i is the solar radiation intensity function value of the i-th collection point, I j is the solar radiation intensity function value of the jth collection point.

[0028] Optionally, the calculation formula of the vertical angle of the real-time radiation incident angle is: Where φ is the vertical angle, is the z-axis weighted partial derivative of solar radiation; the calculation formula of the z-axis weighted partial derivative of solar radiation is:

[0029] Optionally, the calculation formula of the adjustment index is: Among them, M is the adjustment index, W is the wind speed, D is the wind direction angle, U is the shielding ratio, T g is the temperature of the photovoltaic module, and T is the air temperature.

[0030] According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects: the photovoltaic system tracking method based on the astronomical tracking algorithm provided by the present invention comprises: obtaining historical environmental data and real-time environmental data; calculating the light quality score according to the historical environmental data and the real-time environmental data respectively, and taking the percentage of the ratio of the light quality score of the current environmental data to the light quality score of the historical environmental data as the standard for dividing the weather types; calculating the solar altitude angle and the solar azimuth at the current moment and the next moment respectively according to the astronomical algorithm, and generating the solar motion trajectory through the solar altitude angle and the solar azimuth; selecting different photovoltaic module tracking methods according to different weather types. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0032] Figure 1 This is a flow chart of a photovoltaic system tracking method based on an astronomical tracking algorithm according to an embodiment of the present invention;

[0033] Figure 2 A flow chart for selecting tracking methods for different weather types according to an embodiment of the present invention;

[0034] Figure 3 This is a flow chart of a sunny weather control method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0035] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0036] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and understandable, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0037] like Figure 1As shown, an embodiment of the present invention provides a photovoltaic system tracking method based on an astronomical tracking algorithm, comprising the following steps:

[0038] Step 100: Acquire historical environmental data and real-time environmental data.

[0039] Specifically, environmental data include: air quality, air temperature, air humidity, light intensity, total cloud cover, air clarity and air visibility. Historical environmental data refers to monitoring data from the past two years.

[0040] Step 200: Calculate the lighting quality scores according to the historical environmental data and the real-time environmental data respectively, and use the percentage of the lighting quality score of the current environmental data to the lighting quality score of the historical environmental data as a standard for classifying weather types.

[0041] Specifically, the area where this implementation is located is an area with sufficient sunlight and clear weather all year round (for example: the Qinghai-Tibet Plateau). The sunlight time in this type of area is long, the amount of sunlight is sufficient, and it is sunny or with few clouds all year round. An assessment is made of the daily weather conditions based on the daily environmental data. The assessment result (i.e., the light quality score) reflects the degree of sunlight on that day. Since the light intensity is different under different weather conditions, the assessment result can also represent the weather conditions of the day. Then take the average value of the evaluation results. The weather conditions represented by the average value are the critical point between sunny and few-cloud weather conditions. The calculation formula for the light quality score of the current environmental data is:

[0042]

[0043] Among them, S1 is the light quality score of the current environmental data, k is the air quality, T is the air temperature, H is the air humidity, L is the light intensity, C is the total cloud cover, Q is the air clarity, V is the air visibility, and α, β, γ, δ, ε and ∈ are all weight coefficients.

[0044] The calculation formula for the lighting quality score of historical environmental data is:

[0045]

[0046] Among them, S2 is the lighting quality score of historical environmental data, k i is the air quality of the ith historical environmental data, T i is the air temperature of the ith historical environmental data, H i is the air humidity of the ith historical environmental data, L i is the light intensity of the i-th historical environmental data, C i is the total cloud cover of the i-th historical environmental data, Q i is the air clarity of the i-th historical environmental data, V iis the air visibility of the ith historical environmental data, and n is the number of historical environmental data. In this embodiment, preferably α is 0.3, β is 0.1, γ is 0.8, δ is 0.6, ε is 0.4, and ∈ is 0.5.

[0047] More specifically, the weather types are divided into sunny weather, cloudy weather and overcast weather according to the percentage N of the ratio of the light quality score of the current environment data to the light quality score of the historical environment data. The specific classification criteria are:

[0048] When N < 35%, the current weather type is classified as cloudy weather;

[0049] When 35%≤N<70%, the current weather type is classified as cloudy weather;

[0050] When 70%≤N percentage is greater than or equal to seventy percent, the current weather type is classified as sunny weather.

[0051] It should be noted that solar radiation is the main factor affecting the power generation of photovoltaic systems, which is mainly determined by the light intensity. The actual amount of solar radiation received by the photovoltaic system does not entirely depend on the light intensity emitted by the sun. Sunlight will be absorbed by particles in the air and blocked by clouds during propagation. Temperature also has a significant impact on the power generation efficiency of photovoltaic systems. Therefore, combining multiple factors to classify weather types improves the accuracy of weather type identification.

[0052] Step 300: Calculate the solar altitude angle and solar azimuth at the current moment and the next moment respectively according to an astronomical algorithm, and generate the solar motion trajectory through the solar altitude angle and solar azimuth.

[0053] Specifically, first convert the date and time to Julian day and calculate the sun's declination based on the Julian day. Then calculate the local time and get the hour angle from it. Then use the hour angle and declination and use trigonometric functions to calculate the sun's altitude angle, and then get the zenith angle. Calculate the solar azimuth angle based on the solar altitude angle, zenith angle and solar declination. Finally, get the sun's motion trajectory based on the solar altitude angle and solar azimuth angle.

[0054] Step 400: Select different photovoltaic module tracking methods according to different weather types.

[0055] Specific as Figure 2 As shown, according to different weather types, you can choose not to track, track according to the sun's motion trajectory, or track according to the PV module status and the sun's motion trajectory. The specific options include:

[0056] When the weather type is cloudy, the tracking mode of the PV modules is no tracking.

[0057] When the weather type is cloudy, the tracking method of the photovoltaic modules is to track according to the movement trajectory of the sun.

[0058] When the weather type is sunny, the tracking method of the photovoltaic modules is to track according to the status of the photovoltaic modules and the movement trajectory of the sun.

[0059] More specifically, when the weather type is cloudy, the photovoltaic module does not rotate, and the tracking angle of the photovoltaic module is set to a tilt angle of 30°, and it is ensured that the system is in a stable working state at this angle.

[0060] It should be noted that on cloudy days, although the intensity of solar radiation is weakened, the fixed tilt angle can still effectively capture scattered light. At the same time, a tilt angle of 30° is generally suitable for a variety of weather conditions throughout the year, especially in high latitudes, and can provide the best seasonal performance, especially in winter and spring. When the angle is fixed, the maintenance and operation of photovoltaic modules becomes simpler, reducing mechanical wear and the probability of failure. This tracking method reduces system complexity, reduces operating and maintenance costs, and maximizes the power generation efficiency of the photovoltaic system on cloudy days, ensuring that energy can be collected stably even under lower light conditions, and enables the photovoltaic system to maintain a certain power generation capacity on cloudy days, providing users with a more reliable energy supply.

[0061] When the weather type is cloudy, the solar incident angle is calculated based on the solar altitude and azimuth obtained by the astronomical algorithm, and the tracking angle of the photovoltaic module is adjusted to be perpendicular to the solar incident angle based on the calculation result. The sun's azimuth at the next moment is predicted based on the sun's movement trajectory, and the current tracking angle is adjusted based on the sun's azimuth at the next moment to ensure that the photovoltaic module remains perpendicular to the new solar incident angle. When the sun sets, the tracking angle of the photovoltaic module is adjusted to a fixed 30° tilt angle for cloudy weather.

[0062] It should be noted that this tracking method can effectively cope with the changes in light caused by cloudy weather, and try to ensure that the photovoltaic modules are always at the best working angle, thereby improving power generation efficiency. Such adjustments can not only adapt to the impact of clouds on light, but also maximize the capture of scattered light in different time periods, improving the practicality and flexibility of the components. By maximizing the use of light, the photovoltaic system can achieve a higher energy collection rate in cloudy weather, ensure the continuity and stability of power generation, and ensure that users can still obtain a reliable power supply under changing climate conditions. In addition, precise tracking and adjustment can also help reduce the overall output fluctuations of the system and improve the economic benefits of photovoltaic power generation.

[0063] When the weather type is sunny, the tracking method of the photovoltaic module is to track the photovoltaic module status and the sun's movement trajectory. The specific steps are as follows: Figure 3 As shown, including:

[0064] Step 401: Calculate the real-time radiation incident angle according to the real-time solar radiation intensity collected by the photovoltaic module.

[0065] Specifically, light sensors are first installed at multiple adjacent collection points in the photovoltaic module to collect solar radiation intensity data at each collection point. Then, the horizontal and vertical partial derivatives of each collection point are calculated based on the solar radiation intensity data. Then, the horizontal and vertical weighted partial derivatives of each collection point are calculated through the horizontal and vertical partial derivatives. Finally, the real-time radiation incident angle of the photovoltaic module is obtained based on the horizontal and vertical weighted partial derivatives. The calculation formula for the horizontal angle of the real-time radiation incident angle is:

[0066]

[0067] Where θ is the horizontal angle, is the y-axis weighted partial derivative of solar radiation, is the x-axis weighted partial derivative of solar radiation.

[0068] The calculation formula of the y-axis weighted partial derivative of solar radiation is:

[0069]

[0070] The calculation formula of the x-axis weighted partial derivative of solar radiation is:

[0071]

[0072] Where n is the number of collection points for collecting real-time solar radiation intensity, I i is the solar radiation intensity function value of the i-th collection point, I j is the solar radiation intensity function value of the jth collection point.

[0073] It should be noted that the intensity and angle of solar radiation may vary due to terrain, shading and climate change. Therefore, integrating data from multiple collection points can provide more accurate calculations of the angle of incidence and ensure that all components are working under optimal conditions. Through accurate measurement and calculation, the tracking angle of photovoltaic components can be adjusted more effectively to maximize energy conversion and utilization.

[0074] Step 402: Calculate the shading ratio according to the real-time power change of the photovoltaic module.

[0075] Specifically, the unobstructed maximum power output value of the photovoltaic module is first obtained, and then the percentage of the ratio of the difference between the real-time power output value and the unobstructed maximum power output value to the unobstructed maximum power output value is taken as the obstruction ratio.

[0076] It should be noted that the output power of a photovoltaic system directly reflects its energy collection efficiency, and photovoltaic modules that are shaded will show lower power output. By real-time monitoring and calculating the shading ratio, the system can promptly identify and respond to shading problems, thereby improving power generation efficiency. Accurately calculating the shading ratio helps optimize system maintenance plans and ensure that photovoltaic modules always operate under optimal working conditions. In addition, by adjusting the tracking angle of photovoltaic modules to reduce the shading area between photovoltaic modules, the energy loss caused by shading can be reduced, which can significantly improve the system's power generation efficiency and economic returns, making the photovoltaic power generation system more sustainable and profitable in the long run.

[0077] Step 403: Calculate the adjustment index according to the real-time radiation incident angle, the shielding ratio, the temperature of the photovoltaic module, the wind speed and direction, and the air temperature, and adjust the tracking angle in cloudy weather according to the adjustment index to obtain the tracking angle in sunny weather.

[0078] Specifically, the calculation formula of the vertical angle of the real-time radiation incident angle is: Where φ is the vertical angle, is the z-axis weighted partial derivative of solar radiation. The calculation formula of the z-axis weighted partial derivative of solar radiation is:

[0079] The calculation formula of the adjustment index is: Among them, M is the adjustment index, W is the wind speed, D is the wind direction angle, U is the shielding ratio, T g is the temperature of the photovoltaic module, and T is the air temperature.

[0080] More specifically, multiple adjustment indicators are obtained based on the transformation of the real-time radiation incident angle, shielding ratio, temperature of the photovoltaic module, wind speed and direction, and air temperature, and a change curve of the adjustment indicator is generated. Then, the maximum value of the change curve of the adjustment indicator is selected as the adjustment standard, and the tracking angle of the photovoltaic module is adjusted to an angle that makes the adjustment indicator the maximum value.

[0081] The beneficial effects of the present invention are as follows:

[0082] 1) Through the analysis of historical and real-time environmental data, it is possible to accurately evaluate the light quality under different weather conditions, thereby optimizing the operating status of the photovoltaic system and maximizing the use of solar energy under different weather types;

[0083] 2) By accurately calculating the solar altitude and azimuth, the solar movement trajectory is generated to ensure that the photovoltaic modules receive sunlight at the optimal angle, which significantly improves the power generation efficiency.

[0084] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0085] The present invention uses specific examples to illustrate the principles and implementation methods of the present invention. The above examples are only used to help understand the method and core ideas of the present invention. At the same time, for those skilled in the art, according to the ideas of the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A photovoltaic system tracking method based on an astronomical tracking algorithm, characterized in that: The steps include: Obtain historical and real-time environmental data; Calculating the illumination quality scores respectively according to the historical environmental data and the real-time environmental data, and taking the percentage of the illumination quality score of the current environmental data to the illumination quality score of the historical environmental data as the standard for classifying weather types; the weather types include: sunny weather, cloudy weather and overcast weather; Calculate the solar altitude angle and solar azimuth at the current moment and the next moment respectively according to the astronomical algorithm, and generate the solar motion trajectory through the solar altitude angle and solar azimuth; Different photovoltaic component tracking modes are selected according to different weather types; the tracking modes include: no tracking, tracking according to the sun's motion trajectory, and tracking according to the photovoltaic component state and the sun's motion trajectory.

2. The photovoltaic system tracking method based on astronomical tracking algorithm according to claim 1, characterized in that: The calculation formula of the illumination quality score of the current environment data is: Wherein, S1 is the light quality score of the current environmental data, k is the air quality, T is the air temperature, H is the air humidity, L is the light intensity, C is the total cloud cover, Q is the air clarity, V is the air visibility, and α, β, γ, δ, ε and ∈ are all weight coefficients; The calculation formula for the lighting quality score of the historical environmental data is: Where S2 is the light quality score of the historical environmental data, k i is the air quality of the ith historical environmental data, T i is the air temperature of the ith historical environmental data, H i is the air humidity of the ith historical environmental data, L i is the light intensity of the i-th historical environmental data, C i is the total cloud cover of the i-th historical environmental data, Q i is the air clarity of the i-th historical environmental data, V i is the air visibility of the i-th historical environmental data, and n is the number of historical environmental data.

3. The photovoltaic system tracking method based on astronomical tracking algorithm according to claim 1, characterized in that: The percentage of the ratio of the illumination quality score of the current environment data to the illumination quality score of the historical environment data is used as a standard for classifying weather types, and the specific steps include: When the percentage is less than thirty-five percent, the current weather is determined to be cloudy; When the percentage is greater than or equal to 35 percent and less than 70 percent, the current weather is determined to be cloudy weather; When the percentage is greater than or equal to seventy percent, the current weather is determined to be sunny.

4. The photovoltaic system tracking method based on astronomical tracking algorithm according to claim 1, characterized in that: Different photovoltaic module tracking methods are selected according to different weather types. The specific steps include: When the weather type is the cloudy weather, the tracking mode of the photovoltaic module is no tracking; When the weather type is the cloudy weather, the photovoltaic assembly is tracked according to the sun's motion trajectory; When the weather type is the sunny weather, the photovoltaic component is tracked according to the photovoltaic component state and the sun's movement trajectory.

5. The photovoltaic system tracking method based on astronomical tracking algorithm according to claim 4, characterized in that: When the weather type is the cloudy weather, the tracking mode of the photovoltaic component is no tracking, and the specific steps are: when the weather type is the cloudy weather, the photovoltaic component does not rotate, and the tracking angle of the photovoltaic component is fixed at 30°.

6. The photovoltaic system tracking method based on astronomical tracking algorithm according to claim 5, characterized in that: When the weather type is cloudy weather, the tracking method of the photovoltaic component is to track according to the sun's movement trajectory. The specific steps are: when the weather type is cloudy weather, the current tracking angle of the photovoltaic component is kept perpendicular to the incident angle of sunlight, the sun's position at the next moment is predicted by the sun's movement trajectory, and the current tracking angle is adjusted according to the sun's position at the next moment; when the sun sets, the photovoltaic component is adjusted to the tracking method of the cloudy weather.

7. The photovoltaic system tracking method based on astronomical tracking algorithm according to claim 6, characterized in that: When the weather type is sunny, the photovoltaic module is tracked according to the photovoltaic module state and the sun's motion trajectory, and the specific steps include: Calculating a real-time radiation incident angle according to the real-time solar radiation intensity collected by the photovoltaic module; Calculating the shading ratio according to the real-time power change of the photovoltaic module; An adjustment index is calculated according to the real-time radiation incident angle, the shielding ratio, the temperature of the photovoltaic module, the wind speed and direction, and the air temperature, and the tracking angle of the cloudy weather is adjusted according to the adjustment index to obtain a sunny day tracking angle.

8. The photovoltaic system tracking method based on astronomical tracking algorithm according to claim 7, characterized in that: The calculation formula of the horizontal angle of the real-time radiation incident angle is: Wherein, θ is the horizontal angle, is the y-axis weighted partial derivative of solar radiation, is the x-axis weighted partial derivative of solar radiation; the calculation formula of the y-axis weighted partial derivative of solar radiation is: The calculation formula of the x-axis weighted partial derivative of the solar radiation is: Wherein, n is the number of collection points for collecting the real-time solar radiation intensity, I i is the solar radiation intensity function value of the i-th collection point, I j is the solar radiation intensity function value of the jth collection point.

9. The photovoltaic system tracking method based on astronomical tracking algorithm according to claim 7, characterized in that: The calculation formula of the vertical angle of the real-time radiation incident angle is: Wherein, φ is the vertical angle, is the z-axis weighted partial derivative of solar radiation; the calculation formula of the z-axis weighted partial derivative of solar radiation is:

10. The photovoltaic system tracking method based on astronomical tracking algorithm according to claim 9, characterized in that: The calculation formula of the adjustment index is: Wherein, M is the adjustment index, W is the wind speed, D is the wind direction angle, U is the shielding ratio, T g is the temperature of the photovoltaic module, and T is the air temperature.

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