Photovoltaic inclination angle dynamic cooperative adjustment system and method of mobile wind-solar-storage all-in-one machine

Abstract

The invention discloses a system and a method for dynamically and cooperatively adjusting a photovoltaic inclination angle of a mobile wind-solar-storage all-in-one machine. Comprising a multi-source data acquisition module which comprises a GPS positioning unit, a distributed light intensity sensor array, a wind speed and direction sensor and a tilt angle sensor; and the dynamic calculation module is used for calculating the solar altitude according to the positioning information of the GPS positioning unit and the time information, and establishing a quadratic relation model of the irradiance and the incident angle through actual measurement data fitting, so that the irradiance is calculated according to the solar altitude. Environmental parameters are acquired in real time through the multi-source data acquisition module, the optimal irradiance dip angle is determined in combination with the dynamic calculation module, the wind-solar collaborative optimization module dynamically balances the influence of the dip angle of the photovoltaic panel on the air duct of the straight-axis fan, the total power generation amount is maximized, and through real-time monitoring of the environmental parameters, the power generation efficiency is improved. Real-time adjustment is carried out according to weather condition changes, and power generation efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of clean energy, and particularly to a photovoltaic tilt dynamic collaborative regulation system and method for a mobile wind-solar-storage integrated machine. Background Art

[0002] With the transformation of the global energy structure and the growth of emergency power demand, mobile wind-solar-storage integrated machines have shown important value in power supply scenarios in remote areas.

[0003] A mobile wind-solar-storage integrated machine is a mobile integrated energy device integrating wind power generation, photovoltaic power generation, and energy storage systems, designed for scenarios such as emergency power supply, field operations, and temporary power use. Its core feature is integrating the three major energy modules of wind, light, and storage into a transportable box structure, achieving efficient power generation and stable power supply through intelligent collaborative control, breaking through the limitations of traditional fixed new energy power stations.

[0004] Existing mobile wind-solar-storage integrated machines have the following technical pain points: Space conflict: When the photovoltaic panel and the vertical-axis wind turbine are in the same box structure, too large an inclination angle of the photovoltaic panel will block the air inlet channel of the wind turbine, resulting in reduced wind energy power generation efficiency; Insufficient environmental adaptability: The fixed inclination angle scheme cannot be dynamically adjusted in mobile scenarios with multiple environmental changes and weather change scenarios such as rain, overcast, and strong winds, and the total power generation fluctuates violently; Control fragmentation: The traditional system controls wind and light power generation equipment independently, lacking a collaborative optimization mechanism; Therefore, the present invention proposes a photovoltaic tilt dynamic collaborative regulation system and method for a mobile wind-solar-storage integrated machine. Summary of the Invention

[0005] The purpose of the present invention is to solve the deficiencies in the prior art, and to propose a photovoltaic tilt dynamic collaborative regulation system and method for a mobile wind-solar-storage integrated machine.

[0006] To achieve the above purpose, the present invention adopts the following technical solutions: A photovoltaic tilt dynamic collaborative regulation system for a mobile wind-solar-storage integrated machine, comprising: A multi-source data acquisition module, including a GPS positioning unit, a distributed light intensity sensor array, a wind speed and direction sensor, and an inclination angle sensor; A dynamic calculation module, which calculates the solar altitude angle through the positioning information and time information of the GPS positioning unit, and establishes a quadratic relationship model between irradiance and incident angle by fitting the measured data, so as to calculate the irradiance from the solar altitude angle; A wind-light collaborative optimization module, which constructs a weighted objective function including a matrix of inclination-irradiance influence coefficients and a matrix of inclination-wind field influence coefficients, and performs an optimization solution on the function; An intelligent execution module, which is used to adjust the inclination angle of the mobile wind-solar-storage integrated machine, adopts a double-degree-of-freedom self-locking electric push rod, and adjusts the inclination angle according to the optimal solution result; A safety protection module, which monitors weather data in real time. When the monitored weather data enters an extreme weather condition, it enters the equipment protection mode.

[0007] Preferably: The distributed light intensity sensor array adopts an asymmetric arrangement strategy, with 8-12 sensors arranged per square meter in the edge area of the photovoltaic panel and 15-20 sensors arranged in the folding joint area.

[0008] A method for dynamically coordinated adjustment of the photovoltaic inclination angle of a mobile wind-solar-storage integrated machine, comprising the following steps: S1: After the dynamic coordinated adjustment system of the photovoltaic inclination angle is started and run, the current environmental conditions are collected through the multi-source data acquisition module, the current longitude and latitude are obtained, and the current solar altitude angle and azimuth angle are calculated, and according to the solar altitude angle and azimuth angle , when the inclination angle of the photovoltaic panel is ( , ), the included angle between the sun ray and the normal line of the photovoltaic panel, that is, the incident angle is calculated; S2: By adjusting the inclination angle of the photovoltaic panel, different altitude angles and azimuth angles are obtained, and the corresponding incident angle is calculated for each of them. Then, based on the measured data, the relationship curve between the irradiance and the incident angle is fitted, the irradiance is predicted using the fitting model, and the inclination-irradiance influence coefficient matrix M ( , ) is constructed; S3: Evaluate the light energy weight factor and the wind energy weight factor according to the current ambient light intensity G and the ambient wind intensity V; S4: According to the pre-experiment, the inclination-wind field influence coefficient matrix C ( , ) is obtained, which represents the influence of different photovoltaic panel inclination angles on the wind power generation efficiency of the wind turbine; S5: Allocate the weighted contributions of light energy and wind energy to the inclination-irradiance influence coefficient matrix and the inclination-wind field influence coefficient matrix obtained from the pre-experiment, and integrate them into the objective function of maximizing the total power generation: ( , ) = ( , ) + ( , ); S6: Solve the optimal solution of the objective function using the simulated annealing algorithm, and lock the photovoltaic panel at the optimal tilt angle through the intelligent adjustment module; S7: Set the update logic. When the variable reaches the update logic, repeat steps S3 - S6 again; S8: The safety protection module monitors the weather data in real - time. When the monitored weather data enters the extreme weather condition, enter the device protection mode.

[0009] Preferably: In step S1, the calculation formula for the incident angle is: cos( ) = sin( ) cos( ) + cos( ) sin( ) cos( - ).

[0010] Preferably: In step S2, the relationship curve between the fitted irradiance and the incident angle is: ( ) = , where , , are undetermined coefficients determined by multiple groups of data obtained by changing the tilt angle.

[0011] Preferably: In step S3, , , are the wind - solar energy conversion coefficients, used to balance the relative importance of light energy and wind energy.

[0012] Preferably: In step S6, the algorithm logic for the optimal solution is: S61: Generate a random initial solution , define the initial temperature , the cooling coefficient , and the minimum temperature ; S62: Randomly generate a new solution ( , ) near the current solution ( , ); S63: When > 0, it means the new solution is better than the current solution, and directly accept the new solution; when 0, then accept the new solution with a probability of where = - ; S64: Cooling: , repeat the iteration and stop when the temperature is less than the lowest temperature.

[0013] Preferably: In the S7 step, the update logic is time, specifically: set the update time period , when the time interval from the last optimization time is trigger the update.

[0014] Preferably: In the S7 step, the update logic is environmental change, specifically: set the environmental change amplitude percentage threshold , when the change rate of real-time environmental data or time-period average data relative to the environmental data of the last update and optimization exceeds , trigger the update, where the environment is irradiance or wind speed.

[0015] Preferably: In the S8 step, a three-level response mechanism is adopted: First-level response, when the wind speed ≤ 15 m / s, start the dynamic counterweight balance; Second-level response, when the rainfall ≥ 50 mm / h or the visibility ≤ 100 m, flatten the photovoltaic panel to α = 0°; Third-level response, when the wind speed ≥ 25 m / s, completely retract the photovoltaic panel into the box body.

[0016] The beneficial effects of the present invention are: The present invention obtains environmental parameters in real time through the multi-source data acquisition module, determines the optimal irradiance inclination angle in combination with the dynamic calculation module, and the wind-solar collaborative optimization module dynamically balances the influence of the inclination angle of the photovoltaic panel on the direct-axis fan air duct, realizing the maximization of the total power generation. And through the real-time monitoring of environmental parameters, it is adjusted in real time according to the change of weather conditions, improving the power generation efficiency, and protecting the stability of the mobile wind-solar-storage integrated machine under extreme weather conditions, which can effectively improve the total power generation of the mobile wind-solar-storage integrated machine and is widely applied to the mobile energy scenarios in remote areas. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 is the logic diagram of the photovoltaic inclination dynamic collaborative adjustment method of the mobile wind-solar-storage integrated machine proposed by the present invention; Figure 2Logic diagram of the safety protection module according to the environment update in the photovoltaic inclination dynamic collaborative adjustment method of the mobile integrated wind-solar-storage device proposed by the present invention. Detailed implementation manners

[0018] The technical solution of the present invention will be further described in detail below in conjunction with the specific implementation manners.

[0019] In the description of the present invention, it should be noted that unless otherwise clearly specified and limited, the terms "installation", "connection", "connection", and "setting" should be understood in a broad sense. For example, it can be fixedly connected and set, or detachably connected and set, or integrally connected and set. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations.

[0020] Embodiment 1: The photovoltaic inclination dynamic collaborative adjustment system of the mobile integrated wind-solar-storage device includes: The multi-source data acquisition module includes a GPS positioning unit, a distributed light intensity sensor array, a wind speed and direction sensor, and an inclination sensor; The dynamic calculation module calculates the solar altitude angle through the positioning information and time information of the GPS positioning unit, and establishes a quadratic relationship model between irradiance and incident angle by fitting the measured data, so as to calculate the irradiance from the solar altitude angle; The wind-solar collaborative optimization module constructs a weighted objective function including a matrix of inclination-irradiance influence coefficients and a matrix of inclination-wind field influence coefficients, and performs an optimization solution on the function; The intelligent execution module is used to adjust the inclination of the mobile integrated wind-solar-storage device, adopts a double-degree-of-freedom self-locking electric push rod, and adjusts the inclination according to the optimization solution result; The safety protection module monitors the weather data in real time, and enters the device protection mode when the monitored weather data enters the extreme weather condition.

[0021] The distributed light intensity sensor array adopts an asymmetric arrangement strategy, with 8-12 sensors arranged per square meter in the edge area of the photovoltaic panel and 15-20 sensors arranged in the folding joint area.

[0022] Embodiment 2: The photovoltaic inclination dynamic collaborative adjustment method of the mobile integrated wind-solar-storage device includes the following steps: S1: After the photovoltaic inclination dynamic collaborative adjustment system is started and runs, the current environmental conditions will be collected through the multi-source data acquisition module, the current longitude and latitude will be obtained, and the current solar altitude angle and azimuth angle will be calculated in combination with the time information, and according to the solar altitude angle and azimuth angle Calculate the angle between the sun's rays and the normal of the PV panel, i.e., the angle of incidence , ), when the tilt angle of the PV panel is ( ; S2: By adjusting the tilt angle of the PV panel, different altitude angles and azimuth angles are obtained, and the corresponding angle of incidence is calculated. Then, based on the measured data, the relationship curve between irradiance and the angle of incidence is fitted, and the irradiance is predicted using the fitting model to construct the tilt-irradiance influence coefficient matrix M ( , ); S3: Evaluate the light energy weight factor and the wind energy weight factor according to the current ambient light intensity G and ambient wind intensity V; S4: Obtain the tilt-wind field influence coefficient matrix C ( , ) from the pre-experiment, which represents the influence of different tilt angles of the PV panel on the wind energy generation efficiency of the wind turbine; S5: Allocate the weighted contributions of light energy and wind energy to the tilt-irradiance influence coefficient matrix and the tilt-wind field influence coefficient matrix obtained from the pre-experiment, and integrate them into the objective function of maximizing the total power generation: ( , ) = ( , ) + ( , ); S6: Use the simulated annealing algorithm to solve the optimal solution of the objective function, and lock the PV panel at the optimal tilt angle through the intelligent adjustment module; S7: Set the update logic, and when the variable reaches the update logic, repeat steps S3 - S6; S8: The safety protection module monitors the weather data in real time. When the monitored weather data enters the extreme weather condition, enter the equipment protection mode.

[0023] In the step S1, the calculation formula for the angle of incidence is: cos( ) = sin( ) cos( ) + cos( ) sin( ) cos( - )。

[0024] In step S2, the relationship curve between the fitted irradiance and the incident angle is: ( ) = , where , , are undetermined coefficients determined by multiple sets of data obtained by changing the inclination angle.

[0025] In step S3, , , is the wind-solar energy conversion coefficient, which is used to balance the relative importance of light energy and wind energy.

[0026] In step S6, the algorithm logic of the optimal solution is: S61: Generate a random initial solution , define the initial temperature , the cooling coefficient , the minimum temperature ; S62: Randomly generate a new solution ( , ) near the current solution ( , ); S63: When > 0, it means the new solution is better than the current solution, and directly accept the new solution; when 0, then accept the new solution with a probability of , where = - ; S64: Cool down: , repeat the iteration and stop when the temperature is less than the minimum temperature.

[0027] In step S7, the update logic is time, specifically: set the update time period , when the time interval from the last optimization is trigger the update.

[0028] In step S8, a three-level response mechanism is adopted: First-level response, when the wind speed ≤ 15 m / s, start the dynamic counterweight balance; Secondary response: When the rainfall ≥ 50 mm / h or the visibility ≤ 100 m, the photovoltaic panel is flattened to α = 0°; Tertiary response: When the wind speed ≥ 25 m / s, the photovoltaic panel is fully retracted into the box.

[0029] Example 3: A method for dynamically coordinating the inclination angle of a photovoltaic panel of a mobile wind-solar-storage integrated machine, which includes the following steps: S1: After the dynamic coordination adjustment system of the photovoltaic inclination angle is started and run, the current environmental conditions are collected through a multi-source data acquisition module, the current longitude and latitude are obtained, and the current solar altitude angle and azimuth are calculated in combination with the time information, and according to the solar altitude angle and azimuth , when the inclination angle of the photovoltaic panel is ( , ), the included angle between the sun ray and the normal line of the photovoltaic panel, that is, the incident angle is calculated; S2: By adjusting the inclination angle of the photovoltaic panel, different altitude angles and azimuths are obtained, and the corresponding incident angle is calculated for each of them. Then, based on the measured data, the relationship curve between the irradiance and the incident angle is fitted, and the irradiance is predicted using the fitting model to construct the inclination angle-irradiance influence coefficient matrix M ( , ); S3: Evaluate the light energy weight factor and the wind energy weight factor according to the current ambient light intensity G and the ambient wind intensity V; S4: According to the pre-experiment, obtain the inclination angle-wind field influence coefficient matrix C ( , ), which represents the influence of different photovoltaic panel inclination angles on the wind power generation efficiency of the fan; S5: Allocate the weighted contributions of light energy and wind energy to the inclination angle-irradiance influence coefficient matrix and the inclination angle-wind field influence coefficient matrix obtained from the pre-experiment, and integrate them into the total power generation maximization objective function: ( , ) = ( , ) + ( , ); S6: Solve the optimal solution of the objective function using the simulated annealing algorithm, and lock the photovoltaic panel at the optimal tilt angle through the intelligent adjustment module; S7: Set the update logic. When the variable reaches the update logic, repeat steps S3 - S6 again; S8: The safety protection module monitors the weather data in real time. When the monitored weather data enters the extreme weather condition, enter the device protection mode.

[0030] In the S1 step, the calculation formula for the incident angle is: cos( ) = sin( ) cos( ) + cos( ) sin( ) cos( - )。

[0031] In the S2 step, the relationship curve between the fitting irradiance and the incident angle is: ( ) = , where , , are undetermined coefficients determined by multiple groups of data obtained by changing the tilt angle.

[0032] In the S3 step, , , is the wind - solar energy conversion coefficient, which is used to balance the relative importance of light energy and wind energy.

[0033] In the S6 step, the algorithm logic of the optimal solution is: S61: Generate a random initial solution , define the initial temperature , the cooling coefficient , the minimum temperature ; S62: Randomly generate a new solution ( , ) near the current solution ( , ); S63: When > 0, it means the new solution is better than the current solution, and directly accept the new solution; when 0, then with a probability of The probability of accepting a new solution, where = - ; S64: Cooling: , repeat the iteration and stop when the temperature is lower than the lowest temperature.

[0034] In the S7 step, the update logic is environmental change, specifically: set the percentage threshold of the environmental change range , when the change rate of the real-time environmental data or the period average data relative to the environmental data updated and optimized last time exceeds , trigger the update, where the environment is irradiance.

[0035] In the S8 step, a three-level response mechanism is adopted: First-level response, when the wind speed ≤ 15 m / s, start the dynamic counterweight balance; Second-level response, when the rainfall ≥ 50 mm / h or the visibility ≤ 100 m, flatten the photovoltaic panel to α = 0°; Third-level response, when the wind speed ≥ 25 m / s, completely retract the photovoltaic panel into the box body.

[0036] Example 4: A method for dynamically coordinating the adjustment of the photovoltaic tilt angle of a mobile wind-solar-storage integrated machine, which includes the following steps: S1: After the dynamic coordination adjustment system of the photovoltaic tilt angle is started and operated, the current environmental conditions will be collected through the multi-source data acquisition module, obtain the current longitude and latitude, and calculate the current solar altitude angle and azimuth , and according to the solar altitude angle and azimuth calculate the angle between the sun ray and the normal line of the photovoltaic panel when the photovoltaic panel tilt angle is ( , ), that is, the incident angle ; S2: By adjusting the tilt angle of the photovoltaic panel, obtain different altitude angles and azimuth , and calculate each corresponding incident angle , then fit the relationship curve between the irradiance and the incident angle based on the measured data, use the fitting model to predict the irradiance, and construct the tilt-irradiance influence coefficient matrix M ( , ); S3: Evaluate the light energy weight factor and the wind energy weight factor according to the current environmental light intensity G and the environmental wind intensity V; S4: According to the inclination angle - wind field influence coefficient matrix C obtained from the preliminary experiment ( , ), which represents the influence of different inclination angles of photovoltaic panels on the wind energy power generation efficiency of the wind turbine; S5: Allocate the weighted contributions of light energy and wind energy to the inclination angle - irradiance influence coefficient matrix and the inclination angle - wind field influence coefficient matrix obtained from the preliminary experiment, and integrate them into the objective function of maximizing the total power generation: ( , ) = ( , ) + ( , ); S6: Use the simulated annealing algorithm to solve the optimal solution of the objective function, and lock the photovoltaic panel at the optimal inclination angle through the intelligent adjustment module; S7: Set the update logic. When the variable reaches the update logic, repeat steps S3 - S6 again; S8: The safety protection module monitors the weather data in real - time. When the monitored weather data enters the extreme weather condition, enter the equipment protection mode.

[0037] In the above - mentioned S1 step, the calculation formula for the incident angle is: cos( ) = sin( ) cos( ) + cos( ) sin( ) cos( - ).

[0038] In the above - mentioned S2 step, the relationship curve between the fitted irradiance and the incident angle is: ( ) = , where , , are undetermined coefficients, which are determined by multiple groups of data obtained by changing the inclination angle.

[0039] In the above - mentioned S3 step, , , are the conversion coefficients of wind and light energy, which are used to balance the relative importance of light energy and wind energy.

[0040] In the step S6, the algorithm logic of the optimal solution is as follows: S61: Generate a random initial solution , define the initial temperature , cooling coefficient , minimum temperature ; S62: Randomly generate a new solution near the current solution ( , ) ( , ); S63: When >0, it means the new solution is better than the current solution, and directly accept the new solution; when 0, then accept the new solution with a probability of , where = - ; S64: Reduce the temperature: , repeat the iteration and stop when the temperature is less than the lowest temperature.

[0041] In the step S7, the update logic is environmental change, specifically: set the percentage threshold of environmental change amplitude , when the change rate of real-time environmental data or time-period average data relative to the environmental data updated and optimized last time exceeds , trigger the update, where the environment is wind speed.

[0042] In the step S8, a three-level response mechanism is adopted: First-level response, when the wind speed ≤ 15 m / s, start the dynamic counterweight balance; Second-level response, when the rainfall ≥ 50 mm / h or the visibility ≤ 100 m, the photovoltaic panel is flattened to α = 0°; Third-level response, when the wind speed ≥ 25 m / s, the photovoltaic panel is completely retracted into the box.

[0043] The above is only the preferred specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution and inventive concept of the present invention, makes equivalent substitutions or changes, and all should be covered within the protection scope of the present invention.

Claims

1. The photovoltaic tilt angle dynamic coordinated adjustment system of the mobile wind-solar-storage integrated machine is characterized by: include: Multi-source data acquisition module, including GPS positioning unit, distributed light intensity sensor array, wind speed and direction sensor and tilt sensor; A dynamic calculation module calculates the solar altitude angle through the positioning information and time information of the GPS positioning unit, and establishes a quadratic relationship model between irradiance and incident angle through fitting of measured data, thereby calculating irradiance from the solar altitude angle; The wind-solar collaborative optimization module constructs a weighted objective function including a matrix of inclination angle-irradiance influence coefficient and a matrix of inclination angle-wind field influence coefficient, and optimizes the function; An intelligent execution module is used to adjust the inclination angle of the mobile wind-solar-storage integrated machine, using a dual-degree-of-freedom self-locking electric push rod, and adjusting the inclination angle according to the optimization solution result; The safety protection module monitors weather data in real time. When the monitored weather data enters extreme weather conditions, it enters equipment protection mode.

2. The photovoltaic tilt angle dynamic coordinated adjustment system of the mobile wind-solar-storage integrated machine according to claim 1 is characterized in that: The distributed light intensity sensor array adopts an asymmetric arrangement strategy, arranging 8-12 sensors per square meter in the edge area of ​​the photovoltaic panel and arranging 15-20 sensors in the folding joint area.

3. A method for dynamically coordinating the photovoltaic tilt angle of a mobile wind-solar-storage integrated machine, which is a method for implementing the system for dynamically coordinating the photovoltaic tilt angle of a mobile wind-solar-storage integrated machine according to any one of claims 1 to 2, characterized in that: The following steps are involved: S1: After the photovoltaic tilt angle dynamic coordinated adjustment system is started, the current environmental conditions will be collected through the multi-source data acquisition module to obtain the current longitude and latitude, and the current solar altitude angle will be calculated based on the time information. and azimuth , and according to the solar altitude angle and azimuth Calculate when the photovoltaic panel inclination is ( , ), the angle between the sunlight and the normal of the photovoltaic panel, that is, the angle of incidence ; S2: By adjusting the inclination of the photovoltaic panel, different altitude angles are obtained and azimuth , and calculate each corresponding incident angle , and then fit the radiance and incident angle based on the measured data The relationship curve is used to predict the radiation illumination using the fitting model, and the inclination-radiation illumination influence coefficient matrix M is constructed. , ); S3: Evaluate the light energy weight factor based on the current ambient light intensity G and ambient wind intensity V and wind energy weight factor ; S4: Obtain the inclination angle-wind field influence coefficient matrix C based on the preliminary experiment ( , ), which represents the effect of different photovoltaic panel inclination angles on the wind turbine wind power generation efficiency; S5: The weighted contributions of light energy and wind energy are allocated to the inclination-irradiance influence coefficient matrix and the inclination-wind field influence coefficient matrix obtained from the preliminary experiment, and integrated into the total power generation maximization objective function: ( , )= ( , )+ ( , ); S6: Using simulated annealing algorithm to solve the optimal solution of the objective function, and adjusting the photovoltaic panel to the optimal inclination angle and then locking it through the intelligent adjustment module; S7: Set the update logic. When the variable reaches the update logic, repeat steps S3-S6. S8: The safety protection module monitors weather data in real time. When the monitored weather data enters extreme weather conditions, the device enters protection mode.

4. The method for dynamic coordinated adjustment of photovoltaic tilt angle of a mobile wind-solar-storage integrated machine according to claim 3 is characterized in that: In the step S1, the calculation formula of the incident angle is: cos( )=sin( ) cos( )+cos( ) sin( ) cos( - ).

5. The method for dynamic coordinated adjustment of photovoltaic tilt angle of a mobile wind-solar-storage integrated machine according to claim 3 is characterized in that: In the S2 step, the fitting irradiance With the incident angle The relationship curve is: ( )= ,in , , It is an undetermined coefficient, which is determined by multiple sets of data obtained by changing the inclination angle.

6. The method for dynamic coordinated adjustment of photovoltaic tilt angle of a mobile wind-solar-storage integrated machine according to claim 3 is characterized in that: In the S3 step, , , is the wind-solar energy conversion factor, which is used to balance the relative importance of solar energy and wind energy.

7. The method for dynamic coordinated adjustment of photovoltaic tilt angle of a mobile wind-solar-storage integrated machine according to claim 3 is characterized in that: In step S6, the algorithm logic of the optimal solution is: S61: Generate random initial solution , define the initial temperature ,Cooling coefficient , minimum temperature ; S62: In the current solution ( , ) randomly generates new solutions near ( , ); S63: When >0, indicating that the new solution is better than the current solution, and the new solution is directly accepted; 0, then with probability The probability of accepting a new solution is = - ; S64: Cooling: , the iterations are repeated and stop when the temperature is less than the minimum temperature.

8. The method for dynamic coordinated adjustment of photovoltaic tilt angle of a mobile wind-solar-storage integrated machine according to claim 3 is characterized in that: In the step S7, the update logic is time, specifically: setting the update time period , when the time interval from the last optimization is Trigger an update.

9. The method for dynamic coordinated adjustment of photovoltaic tilt angle of a mobile wind-solar-storage integrated machine according to claim 3 is characterized in that: In the step S7, the update logic is the environment change, specifically: setting the percentage threshold of the environment change amplitude When the real-time environment data or the average data of the period changes more than the last updated environment data When , the update is triggered, where the environment is irradiance or wind speed.

10. The method for dynamic coordinated adjustment of photovoltaic tilt angle of a mobile wind-solar-storage integrated machine according to claim 3, characterized in that: In the S8 step, a three-level response mechanism is adopted: Level 1 response: when the wind speed is ≤15m / s, dynamic counterweight balancing is started; Secondary response: when rainfall is ≥50mm / h or visibility is ≤100m, the photovoltaic panels are flattened to α=0°; Level 3 response: when the wind speed is ≥25m / s, the photovoltaic panels are completely retracted into the box.

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