Photovoltaic power station energy efficiency optimization early warning system based on digital twinning

Abstract

The application discloses a photovoltaic power station energy efficiency optimization early warning system based on digital twinning, relates to the field of power station monitoring optimization, solves the problem that a traditional early warning system cannot accurately identify fault groups in a photovoltaic power station, and leads to a long fault troubleshooting period, and comprises a digital twinning module, a group string detection module, an inclination angle analysis module and a dust accumulation early warning module, the group string detection module is used for detecting the power generation condition of groups in the photovoltaic power station, and if an abnormal instruction is generated in detection, the abnormal instruction is sent to the digital twinning module; the inclination angle analysis module is used for analyzing the component inclination angle of photovoltaic components according to standard component data; the dust accumulation early warning module is used for detecting the operation condition of photovoltaic components, and if a dust accumulation early warning instruction is generated in detection, the dust accumulation early warning instruction is sent to the data twinning module; and the digital twinning module is used for highlighting corresponding groups, component inclination angles and photovoltaic components, and the application realizes intelligent optimization and intelligent early warning of the energy efficiency of the photovoltaic power station.

Description

Technical Field

[0001] This invention belongs to the field of power plant monitoring and optimization technology, specifically a photovoltaic power plant energy efficiency optimization and early warning system based on digital twins. Background Technology

[0002] A photovoltaic (PV) power station is a large-scale energy system that directly converts solar radiation into electrical energy using solar photovoltaic modules. It typically consists of multiple PV module arrays, combiner boxes, inverters, power distribution equipment, and monitoring systems. These systems are centrally located in open areas (such as deserts, factory rooftops, or water surfaces) and the generated electricity is fed into the power grid or supplied to local loads. It is a clean and renewable power generation method that boasts high power generation efficiency and a long operational lifespan under sufficient sunlight conditions.

[0003] In existing technologies, traditional early warning systems rely on station-level data or inverter-level data from photovoltaic power plants, which cannot accurately identify faulty strings within the photovoltaic power plant. This results in long troubleshooting cycles and continuous power generation losses. In addition, existing adjustments to the tilt angle of photovoltaic modules are often based on the direct angle of sunlight, ignoring the problem of dust accumulation on the surface of photovoltaic modules, leading to a reduction in the power generation efficiency of photovoltaic modules.

[0004] To address this, the present invention proposes a photovoltaic power plant energy efficiency optimization and early warning system based on digital twins. Summary of the Invention

[0005] In view of the shortcomings of existing technologies, the purpose of this invention is to provide a photovoltaic power plant energy efficiency optimization and early warning system based on digital twins.

[0006] The technical problem to be solved by this invention is:

[0007] How to intelligently optimize and provide early warnings for the energy efficiency of photovoltaic power plants.

[0008] The objective of this invention can be achieved through the following technical solutions:

[0009] The photovoltaic power plant energy efficiency optimization and early warning system based on digital twins includes a data acquisition module, a digital twin module, a string detection module, a tilt angle analysis module, a dust accumulation early warning module, an execution module, and a database module. The database module is used to store digital twin data and standard component data of the photovoltaic power plant, as well as standard dust accumulation rate and standard power generation data of the photovoltaic components. The digital twin module is used to construct a digital twin model of the photovoltaic power plant.

[0010] The data acquisition module is used to collect real-time power generation data and real-time irradiance of the strings in the photovoltaic power station, as well as the position and tilt angle data of the photovoltaic modules; the string detection module is used to detect the power generation status of the strings in the photovoltaic power station, and if an abnormal command is generated, it is sent to the digital twin module.

[0011] The tilt angle analysis module is used to analyze the tilt angle of the photovoltaic module based on standard module data, and sends the target tilt angle of the photovoltaic module to the digital twin module and the execution module. The actual dust accumulation rate of the photovoltaic module is sent to the dust accumulation early warning module. The execution module is used to adjust the photovoltaic module.

[0012] The dust accumulation warning module is used to detect the operating status of the photovoltaic modules. If a dust accumulation warning command is generated, it is sent to the data twin module. The digital twin module is also used to highlight the corresponding string, module tilt angle and photovoltaic module.

[0013] Furthermore, the digital twin data includes a 3D structural diagram of the photovoltaic modules within the photovoltaic power station, as well as the length and width of the roads.

[0014] Furthermore, the construction process of the digital twin module is as follows:

[0015] Obtain the geometric center point of the photovoltaic power station, take the geometric center point as the origin O, take any direction as the positive X-axis, take the direction perpendicular to the X-axis as the positive Y-axis, and take the direction perpendicular to the plane formed by the X-axis and Y-axis as the positive Z-axis to construct the three-dimensional coordinate system of the photovoltaic power station;

[0016] The digital twin data of the photovoltaic power station is imported into the 3D engine, and the digital twin models of photovoltaic modules, energy storage equipment and roads are constructed through the 3D engine.

[0017] Then, all the coordinates of the digital twin model are obtained and input into the three-dimensional coordinate system of the photovoltaic power station to construct the digital twin model of the photovoltaic power station.

[0018] Furthermore, real-time irradiance is the solar power received by a fixed area of ​​the photovoltaic module;

[0019] Real-time power generation data refers to the real-time current and voltage values ​​of the photovoltaic modules within the string during photovoltaic power generation.

[0020] Furthermore, the detection process of the string detection module is as follows:

[0021] Obtain the real-time current and voltage values ​​of the string, multiply the real-time current and voltage values ​​to obtain the real-time output power of the corresponding string;

[0022] Then, the real-time output power of all strings is obtained, the real-time output power is summed and the average value is taken to obtain the average output power of all strings.

[0023] Finally, the real-time irradiance of the string is obtained, and the standard average output power of all strings is calculated.

[0024] Calculate the power deviation rate of any string. If the power deviation rate of the string is less than the power deviation rate threshold, no operation is performed. If the power deviation rate of the string is greater than or equal to the power deviation rate threshold, the power generation status of the corresponding string is determined to be abnormal, and an abnormal command is issued.

[0025] Furthermore, the standard component data includes the upper limit of dust accumulation weight on the surface of photovoltaic modules when the module tilt angle is 0° within a fixed period of time, the maximum module tilt angle, the minimum module tilt angle, and the surface area of ​​the photovoltaic modules;

[0026] The location tilt angle data includes the straight-line distance between the photovoltaic module and the road, and the real-time tilt angle of the module.

[0027] Furthermore, the analysis process of the tilt angle analysis module is as follows:

[0028] Obtain the upper limit of the dust accumulation weight on the surface of the photovoltaic module and the surface area of ​​the photovoltaic module within a fixed time period, and calculate the maximum dust accumulation rate of the photovoltaic module;

[0029] Then, the straight-line distance between the photovoltaic module and the road, as well as the real-time tilt angle of the photovoltaic module, are obtained to construct a distance-tilt angle model of the photovoltaic module;

[0030] The road distance attenuation index and the inclination effect index in the distance-inclination model are obtained by nonlinear fitting calculation.

[0031] Furthermore, the adjustment process of the tilt analysis module also includes:

[0032] The standard dust accumulation rate of the photovoltaic module and the straight-line distance between the photovoltaic module and the road are obtained. The standard dust accumulation rate is substituted into the actual dust accumulation rate, and the target tilt angle of the photovoltaic module is calculated by combining the straight-line distance and using the distance-tilt angle model.

[0033] If the target module tilt angle is greater than or equal to the maximum module tilt angle, then the target module tilt angle of the corresponding photovoltaic module is set to the maximum module tilt angle;

[0034] If the target component tilt angle is greater than the minimum component tilt angle but less than the maximum component tilt angle, no action will be taken.

[0035] If the target module tilt angle is less than or equal to the minimum module tilt angle, then the target module tilt angle of the corresponding photovoltaic module is set to the minimum module tilt angle.

[0036] Furthermore, standard power generation data refers to the standard current and standard voltage values ​​when photovoltaic modules generate photovoltaic power.

[0037] Furthermore, the working process of the dust accumulation early warning module is as follows:

[0038] Obtain the actual dust accumulation rate of the photovoltaic module and calculate the actual dust accumulation weight of the photovoltaic module at any time point;

[0039] If the dust accumulation weight of the photovoltaic module is greater than or equal to the dust accumulation weight threshold on any day, the photovoltaic module is judged to be operating abnormally, and an early warning command is issued.

[0040] If the dust weight of the photovoltaic module is less than the dust weight threshold at all times, the real-time current value and standard current value of the photovoltaic module are obtained, and the current deviation rate of the corresponding photovoltaic module is calculated. Then, the real-time voltage value and standard voltage value of the photovoltaic module are obtained, and the voltage deviation rate of the corresponding photovoltaic module is calculated. If the current deviation rate is greater than or equal to the current deviation rate threshold, or the voltage deviation rate is greater than or equal to the voltage deviation rate threshold, the real-time dust weight of the corresponding photovoltaic module is determined to be greater than the weight threshold, the operation of the photovoltaic module is abnormal, and a dust accumulation warning command is issued. If the current deviation rate is less than the current deviation rate threshold and the voltage deviation rate is less than the voltage deviation rate threshold, no operation is performed.

[0041] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0042] 1. This invention uses stored digital twin data and constructs a digital twin model of a photovoltaic power station through a data twin module to achieve intelligent and refined display of the photovoltaic power station;

[0043] 2. This invention collects real-time power generation data and real-time irradiance of the strings in a photovoltaic power station. Then, combining the real-time power generation data and real-time irradiance, the string detection module detects the power generation status of the strings in the photovoltaic power station. When an abnormal command is generated, it is sent to the digital twin module, which can highlight the corresponding string.

[0044] 3. This invention combines standard component data of photovoltaic power plants with standard dust accumulation rate and tilt angle data of photovoltaic components. Based on the standard component data, it analyzes the tilt angle of photovoltaic components. When the tilt angle of the target component does not conform to the relationship between the minimum and maximum tilt angles, the tilt angle of the photovoltaic component is adjusted by the execution module. At the same time, the corresponding tilt angle of the component is displayed using a digital twin module.

[0045] 4. This invention uses a dust accumulation early warning module to detect the operating status of photovoltaic modules based on dust accumulation rate and standard power generation data. If a dust accumulation early warning command is generated, it is sent to the data twin module, which then highlights the corresponding photovoltaic module to analyze the dust accumulation status of the photovoltaic module. Attached Figure Description

[0046] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0047] Figure 1 This is an overall system block diagram of the present invention;

[0048] Figure 2 This is an example diagram of a string in this invention;

[0049] Figure 3 This is an example diagram illustrating the straight-line distance between the photovoltaic module and the road in this invention;

[0050] Figure 4 This is a front view of the intelligent combiner box monitoring and control terminal in this invention;

[0051] Figure 5 This is a flowchart of the method of the present invention. Detailed Implementation

[0052] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0053] Example 1, please refer to Figures 1-4 As shown, the technical solution provided by this invention is: a photovoltaic power station energy efficiency optimization and early warning system based on digital twins. This system is used to detect the power generation efficiency of photovoltaic power stations, and to optimize and provide early warnings based on the detection results. It includes a data acquisition module, a digital twin module, a string detection module, a tilt angle analysis module, a dust accumulation early warning module, an execution module, and a database module. Specifically, a string is an electrical unit composed of multiple photovoltaic modules connected in series within the photovoltaic power station.

[0054] In this embodiment, the database module is used to store digital twin data of the photovoltaic power station and send the digital twin data to the digital twin module; wherein, the digital twin data specifically includes a 3D structural diagram of the photovoltaic modules within the photovoltaic power station and the length and width of the roads; specifically, the photovoltaic modules are solar panels;

[0055] In this embodiment, the digital twin module is used to construct a digital twin model of a photovoltaic power station. The construction process is as follows:

[0056] Step A101: Obtain the geometric center point of the photovoltaic power station. Take the geometric center point as the origin O, any direction as the positive X-axis, the direction perpendicular to the X-axis as the positive Y-axis, and the direction perpendicular to the plane formed by the X-axis and Y-axis as the positive Z-axis to construct the three-dimensional coordinate system of the photovoltaic power station.

[0057] Step A102: Import the digital twin data of the photovoltaic power station into the 3D engine, and construct digital twin models of photovoltaic modules, energy storage devices and roads through the 3D engine. Then, obtain the coordinates of the digital twin models and input them into the 3D coordinate system of the photovoltaic power station to construct the digital twin model of the photovoltaic power station.

[0058] Specifically, the 3D engines include Unity, Unreal Engine, and Three.js.

[0059] In this embodiment, the data acquisition module is used to collect real-time power generation data and real-time irradiance of the strings in the photovoltaic power station, and send them to the string detection module and the dust accumulation early warning module.

[0060] Specifically, real-time irradiance refers to the solar power received by a fixed area of ​​the photovoltaic modules, measured in watts per square meter. Real-time power generation data refers to the real-time current and voltage values ​​of the photovoltaic modules within the string during photovoltaic power generation. Specifically, the real-time power generation data of the string can be collected through a smart combiner box monitoring and control terminal. This terminal is suitable for distributed photovoltaic power stations. In practice, the measurement accuracy of the smart combiner box monitoring and control terminal for real-time current is 0.5%, and the measurement accuracy for real-time voltage is 0.5%. The test data table for the smart combiner box monitoring and control terminal is shown in Table 1.

[0061] Table 1:

[0062]

[0063] Specifically, the database module is also used to store the standard irradiance of the string and send the standard irradiance to the string detection module;

[0064] In this embodiment, the string detection module is used to detect the power generation status of the strings in the photovoltaic power station. The detection process is as follows:

[0065] Step B101: Obtain the real-time current and real-time voltage values ​​of the string, multiply the real-time current and real-time voltage values ​​to obtain the real-time output power of the corresponding string.

[0066] Specifically, a string is a group of electrical units formed by connecting a fixed number of photovoltaic modules in series. Each string has an independent output current and voltage channel. Multiple strings are aggregated through a smart combiner box and then connected to an inverter through the smart combiner box.

[0067] Step B102: Obtain the real-time output power SGj of all strings, where j is the string number, j=1, 2, ..., o, and o is a positive integer. Sum the real-time output power and take the average value to obtain the average output power PS of all strings.

[0068] Step B103: Obtain the real-time irradiance G and standard irradiance H of the strings, and calculate the standard average output power BS of all strings using the following formula:

[0069] BS = PS / G × H;

[0070] It should be noted that the standard average output power is specifically the output power of the string under standard irradiance; in practice, H = 1000 W / m².

[0071] Step B104: Calculate the power deviation rate GPj for any string group using the following formula:

[0072] GPj = |SGj - BS| / BS;

[0073] Step B105: When the power deviation rate of the string is less than the power deviation rate threshold, no operation is performed;

[0074] When the power deviation rate of a string is greater than or equal to the power deviation rate threshold, the power generation status of the corresponding string is determined to be abnormal, and an abnormal command is issued.

[0075] The string detection module sends an abnormal command to the digital twin module, which then highlights the corresponding string.

[0076] As a further embodiment, the database module is also used to store standard component data of the photovoltaic power station and the standard dust accumulation rate of the photovoltaic components, and send them to the tilt angle analysis module;

[0077] Specifically, the standard component data includes the upper limit of dust accumulation weight on the surface of photovoltaic modules when the module tilt angle is 0° within a fixed period of time, the maximum module tilt angle, the minimum module tilt angle, and the surface area of ​​the photovoltaic modules; in specific implementation, the fixed period is one week; the standard dust accumulation rate is the maximum daily dust accumulation rate allowed under the premise that the photovoltaic modules can meet the preset minimum power generation performance requirements, which is the existing data.

[0078] Specifically, the data acquisition module is also used to acquire the position tilt angle data of the photovoltaic module and send the position tilt angle data to the tilt angle analysis module;

[0079] Specifically, the location tilt angle data includes the straight-line distance between the photovoltaic module and the road, and the real-time tilt angle of the module.

[0080] In this embodiment, the tilt angle analysis module is used to analyze the tilt angle of the photovoltaic module based on standard module data. The analysis process is as follows:

[0081] Step C101: Obtain the upper limit value ZL of the dust accumulation weight on the surface of the photovoltaic module and the surface area MJ of the photovoltaic module within a fixed time period SC. Calculate the maximum dust accumulation rate SL of the photovoltaic module using the formula as follows: SL=ZL / (MJ×SC), where the unit of the dust accumulation rate of the photovoltaic module is grams per square meter per day.

[0082] Step C102: Obtain the straight-line distance JLi between photovoltaic module i and the road, and the real-time tilt angle αi of the photovoltaic module, and construct the distance-tilt angle model of the photovoltaic module, where i is the number of the photovoltaic module, i=1,2,...,n, and n is a positive integer. The specific model is as follows:

[0083] Where r is the actual dust accumulation rate of the photovoltaic module, e is the natural constant, β is the road distance attenuation index, which reflects the relationship between the road distance of the photovoltaic module and the upper limit of the dust weight, and m is the tilt angle influence index, which reflects the relationship between the real-time tilt angle of the photovoltaic module and the upper limit of the dust weight.

[0084] Step C103 involves calculating the road distance attenuation index and the inclination influence index in the distance-inclination model through nonlinear fitting. The specific steps for performing nonlinear fitting on the distance-inclination model are as follows:

[0085] Constructing a residual function based on the distance-tilt model of photovoltaic modules Then, (β, m) is iteratively updated using a nonlinear optimization algorithm. In each iteration, the Jacobian of the residual pair (β, m) is calculated and the step size is adjusted until the change of (β, m) is less than the parameter change threshold or the change of the residual is less than the residual change threshold. The iteration stops then.

[0086] Step C104: Obtain the standard dust accumulation rate of the photovoltaic module and the straight-line distance between the photovoltaic module and the road. Substitute the standard dust accumulation rate into the actual dust accumulation rate and combine it with the straight-line distance to calculate the target tilt angle of the photovoltaic module using the distance-tilt angle model.

[0087] Step C105: If the target module tilt angle is greater than or equal to the maximum module tilt angle, then set the target module tilt angle of the corresponding photovoltaic module to the maximum module tilt angle;

[0088] If the target component tilt angle is greater than the minimum component tilt angle but less than the maximum component tilt angle, no action will be taken.

[0089] If the target module tilt angle is less than or equal to the minimum module tilt angle, then the target module tilt angle of the corresponding photovoltaic module is set to the minimum module tilt angle;

[0090] The tilt angle analysis module sends the target tilt angle of the photovoltaic module to the digital twin module and the execution module, and at the same time sends the actual dust accumulation rate of the photovoltaic module to the dust accumulation early warning module. The digital twin module is used to display the tilt angle of the module, and the execution module is used to adjust the photovoltaic module. In fact, the execution module is a device component that can adjust the tilt angle of the photovoltaic module.

[0091] Specifically, the database module is also used to store standard power generation data of photovoltaic modules, and simultaneously send the standard power generation data and standard module data to the dust accumulation early warning module;

[0092] Specifically, the standard power generation data refers to the standard current and standard voltage values ​​of the photovoltaic module when it generates photovoltaic power. In this embodiment, the database module only sends the surface area of ​​the photovoltaic module within the standard module data to the dust accumulation warning module.

[0093] In this embodiment, the dust accumulation early warning module is used to detect the operating status of the photovoltaic module based on the dust accumulation rate and standard power generation data. The detection process is as follows:

[0094] Step D101: Obtain the actual dust accumulation rate of the photovoltaic module, and calculate the actual dust accumulation weight Ri(t) of the photovoltaic module at any time point using the formula as follows:

[0095] Ri(t) = Ri(t-1) + ri(t) × Δt × MJ, where t is the time node number, Δt is the unit duration in days, and in practice, Δt = 1; ri(t) is the actual dust accumulation rate of any photovoltaic module at time node number t; the unit of Ri(t) is grams.

[0096] Step D102: If the dust accumulation weight of the photovoltaic module is greater than or equal to the dust accumulation weight threshold on any day, the photovoltaic module is determined to be in abnormal operation, and an early warning command is issued.

[0097] If the dust weight of the photovoltaic module is less than the dust weight threshold at all times, proceed to step D103.

[0098] Step D103: Obtain the real-time current value SLi and the standard current value BL of the photovoltaic module, and calculate the current deviation rate LPi of the corresponding photovoltaic module using the formula as follows:

[0099] LPi = |SLi-BL| / BL;

[0100] Step D104: Obtain the real-time voltage value SYi and the standard voltage value BY of the photovoltaic module, and calculate the voltage deviation rate YPi of the corresponding photovoltaic module using the formula as follows:

[0101] YPi = |SYi-BY| / BY;

[0102] Step D105: If the current deviation rate is greater than or equal to the current deviation rate threshold, or the voltage deviation rate is greater than or equal to the voltage deviation rate threshold, then the real-time dust accumulation weight of the corresponding photovoltaic module is determined to be greater than the weight threshold, the photovoltaic module is in an abnormal operating condition, and a dust accumulation warning command is issued at the same time.

[0103] If the current deviation rate is less than the current deviation rate threshold and the voltage deviation rate is less than the voltage deviation rate threshold, no operation will be performed.

[0104] The dust accumulation warning module sends a dust accumulation warning command to the data twin module, and the data twin module highlights the corresponding photovoltaic module according to the dust accumulation warning command.

[0105] Example 2, as Figure 5 As shown, based on another concept of the same invention, a photovoltaic power plant energy efficiency optimization and early warning method based on digital twins is proposed, including the following steps:

[0106] Step S100: Construct a digital twin model of the photovoltaic power station based on the digital twin data;

[0107] Step S200: Based on real-time power generation data and real-time irradiance, obtain the standard average output power of all strings, and analyze the power deviation rate of the strings in combination with the real-time output power to obtain the power generation status of the corresponding strings.

[0108] Step S300: Adjust the real-time tilt angle of the photovoltaic module to the target tilt angle using standard module data and position tilt angle data;

[0109] Step S400: Based on the dust accumulation rate and standard power generation data, obtain the current deviation rate and voltage deviation rate of the photovoltaic module, analyze the current deviation rate and voltage deviation rate, and obtain the operating status of the photovoltaic module.

[0110] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A photovoltaic power plant energy efficiency optimization and early warning system based on digital twins, characterized in that, It includes a data acquisition module, a digital twin module, a string detection module, a tilt angle analysis module, a dust accumulation early warning module, an execution module, and a database module. The database module is used to store digital twin data and standard component data of the photovoltaic power station, as well as standard dust accumulation rate and standard power generation data of the photovoltaic components. The digital twin module is used to construct a digital twin model of the photovoltaic power station. The data acquisition module is used to collect real-time power generation data and real-time irradiance of the strings in the photovoltaic power station, as well as the position and tilt angle data of the photovoltaic modules; the database module is also used to store the standard irradiance of the strings and send the standard irradiance to the string detection module; the string detection module is used to detect the power generation status of the strings in the photovoltaic power station, and if an abnormal command is generated, it is sent to the digital twin module. The tilt angle analysis module is used to analyze the tilt angle of the photovoltaic module based on standard module data, and sends the obtained target tilt angle of the photovoltaic module to the digital twin module and the execution module. The actual dust accumulation rate of the photovoltaic module is sent to the dust accumulation early warning module. The execution module is used to adjust the photovoltaic module. The analysis process of the tilt angle analysis module is as follows: The maximum dust accumulation rate SL of the photovoltaic module is calculated by obtaining the upper limit value ZL of the dust accumulation weight on the surface of the photovoltaic module and the surface area MJ of the photovoltaic module within a fixed time period SC, and by using the formula SL=ZL / (MJ×SC). Then, the straight-line distance JLi between photovoltaic module i and the road, and the real-time tilt angle αi of the photovoltaic module are obtained to construct a distance-tilt angle model for the photovoltaic module, where i = 1, 2, ..., n, and n is a positive integer. The specific model is as follows: Where r is the actual dust accumulation rate of the photovoltaic module, e is the natural constant, β is the road distance attenuation index, and m is the tilt angle influence index; The road distance attenuation index and the inclination angle influence index in the distance-inclination angle model are obtained by nonlinear fitting. The specific process of performing nonlinear fitting on the distance-inclination angle model is as follows: The residual function is constructed based on the distance-tilt model of photovoltaic modules, and then (β, m) is iteratively updated through a nonlinear optimization algorithm. In each iteration, the Jacobian of the residual pair (β, m) is calculated and the step size is adjusted until the change of (β, m) is less than the parameter change threshold or the change of the residual is less than the residual change threshold, and then the iteration stops. The standard dust accumulation rate of the photovoltaic module and the straight-line distance between the photovoltaic module and the road are obtained. The standard dust accumulation rate is substituted into the actual dust accumulation rate, and the target tilt angle of the photovoltaic module is calculated by combining the straight-line distance and using the distance-tilt angle model. If the target module tilt angle is greater than or equal to the maximum module tilt angle, then the target module tilt angle of the corresponding photovoltaic module is set to the maximum module tilt angle; If the target component tilt angle is greater than the minimum component tilt angle but less than the maximum component tilt angle, no action will be taken. If the target module tilt angle is less than or equal to the minimum module tilt angle, then the target module tilt angle of the corresponding photovoltaic module is set to the minimum module tilt angle; The dust accumulation warning module is used to detect the operating status of the photovoltaic modules. If a dust accumulation warning command is generated, it is sent to the data twin module. The digital twin module is also used to highlight the corresponding string, module tilt angle and photovoltaic module.

2. The photovoltaic power plant energy efficiency optimization and early warning system based on digital twins according to claim 1, characterized in that, Digital twin data consists of 3D structural diagrams of photovoltaic modules within a photovoltaic power station, as well as the length and width of roads.

3. The photovoltaic power plant energy efficiency optimization and early warning system based on digital twins according to claim 2, characterized in that, The construction process of the digital twin module is as follows: Obtain the geometric center point of the photovoltaic power station, take the geometric center point as the origin O, take any direction as the positive X-axis, take the direction perpendicular to the X-axis as the positive Y-axis, and take the direction perpendicular to the plane formed by the X-axis and Y-axis as the positive Z-axis to construct the three-dimensional coordinate system of the photovoltaic power station; The digital twin data of the photovoltaic power station is imported into the 3D engine, and the digital twin models of photovoltaic modules, energy storage equipment and roads are constructed through the 3D engine. Then, all the coordinates of the digital twin model are obtained and input into the three-dimensional coordinate system of the photovoltaic power station to construct the digital twin model of the photovoltaic power station.

4. The photovoltaic power plant energy efficiency optimization and early warning system based on digital twins according to claim 1, characterized in that, Real-time irradiance is the solar power received by a fixed area of ​​a photovoltaic module; Real-time power generation data refers to the real-time current and voltage values ​​of the photovoltaic modules within the string during photovoltaic power generation.

5. The photovoltaic power plant energy efficiency optimization and early warning system based on digital twins according to claim 4, characterized in that, The detection process of the string detection module is as follows: Obtain the real-time current and voltage values ​​of the string, multiply the real-time current and voltage values ​​to obtain the real-time output power of the corresponding string; Then, the real-time output power of all strings is obtained, the real-time output power is summed and the average value is taken to obtain the average output power of all strings. Finally, the real-time irradiance and standard irradiance of the string are obtained, and the standard average output power of all strings is calculated. Calculate the power deviation rate of any string. If the power deviation rate of the string is less than the power deviation rate threshold, no operation is performed. If the power deviation rate of the string is greater than or equal to the power deviation rate threshold, the power generation status of the corresponding string is determined to be abnormal, and an abnormal command is issued.

6. The photovoltaic power plant energy efficiency optimization and early warning system based on digital twins according to claim 1, characterized in that, The standard component data includes the upper limit of dust accumulation on the surface of photovoltaic modules, the maximum tilt angle, the minimum tilt angle, and the surface area of ​​photovoltaic modules when the module tilt angle is 0° within a fixed period of time. The location tilt angle data includes the straight-line distance between the photovoltaic module and the road, and the real-time tilt angle of the module.

7. The photovoltaic power plant energy efficiency optimization and early warning system based on digital twins according to claim 1, characterized in that, Standard power generation data refers to the standard current and standard voltage values ​​when photovoltaic modules generate photovoltaic power.

8. The photovoltaic power plant energy efficiency optimization and early warning system based on digital twins according to claim 7, characterized in that, The working process of the dust accumulation early warning module is as follows: Obtain the actual dust accumulation rate of the photovoltaic module and calculate the actual dust accumulation weight of the photovoltaic module at any time point; If the dust accumulation weight of the photovoltaic module is greater than or equal to the dust accumulation weight threshold on any day, the photovoltaic module is judged to be operating abnormally, and an early warning command is issued. If the dust weight of the photovoltaic module is less than the dust weight threshold at all times, the real-time current value and standard current value of the photovoltaic module are obtained, and the current deviation rate of the corresponding photovoltaic module is calculated. Then, the real-time voltage value and standard voltage value of the photovoltaic module are obtained, and the voltage deviation rate of the corresponding photovoltaic module is calculated. If the current deviation rate is greater than or equal to the current deviation rate threshold, or the voltage deviation rate is greater than or equal to the voltage deviation rate threshold, the real-time dust weight of the corresponding photovoltaic module is determined to be greater than the weight threshold, the operation of the photovoltaic module is abnormal, and a dust accumulation warning command is issued. If the current deviation rate is less than the current deviation rate threshold and the voltage deviation rate is less than the voltage deviation rate threshold, no operation will be performed.

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