Offshore floating type photovoltaic power station digital twinborn monitoring system and method and related equipment

Abstract

The invention relates to the technical field of expert systems, in particular to an offshore floating photovoltaic power station digital twinborn monitoring system and method and related equipment.The monitoring system comprises a physical entity system, a data management system and a virtual digital system.The physical entity system comprises a floating photovoltaic power station physical entity and a data collection module; the data collection module is used for collecting data information through a sensor; the data management system comprises a data processing module and a data transmission module, and the data processing module preprocesses and analyzes acquired data information of the sensor, extracts key features of the data information, normalizes the data and establishes a data processing model. According to the offshore floating type photovoltaic monitoring digital twinning system, through intelligent and digital technologies, the efficiency and reliability of photovoltaic power generation can be improved, the early warning capacity for ocean weather changes can be enhanced, and the equipment state can be conveniently predicted according to environmental factors.

Description

Technical Field

[0001] The present invention relates to the technical field of equipment safety monitoring, and in particular to a digital twin monitoring system for an offshore floating photovoltaic power station. Background Art

[0002] With the transformation of the global energy structure and the growing demand for clean energy, especially driven by the "dual carbon" goal, offshore floating photovoltaic power stations have attracted attention due to their advantages of not occupying land resources and high power generation efficiency. However, the offshore environment is complex and changeable, which puts higher requirements on the monitoring and operation and maintenance of power stations.

[0003] As an emerging technology, digital twin technology creates virtual digital copies of physical entities, realizes seamless connection and data interaction between the physical world and the digital world, enables real-time monitoring and simulation of physical equipment, provides simulation, monitoring, diagnosis, prediction and control functions, and improves operation and maintenance efficiency and safety. However, it has not been applied to offshore floating photovoltaic power stations.

[0004] Therefore, it is urgent to design a digital twin monitoring system, method and related equipment for offshore floating photovoltaic power stations. Summary of the invention

[0005] In response to the problems existing in the background technology, the embodiments of the present invention propose a digital twin monitoring system, method and related equipment for an offshore floating photovoltaic power station, aiming to achieve real-time monitoring and simulation of the offshore floating photovoltaic power station through digital twin technology, so as to solve the problems faced by the offshore floating photovoltaic power station raised by the above background technology.

[0006] The technical solution of the present invention: A digital twin monitoring system for an offshore floating photovoltaic power station, comprising a physical entity system, a data management system and a virtual digital system;

[0007] The physical entity system includes a floating photovoltaic power station physical entity and a data collection module, wherein the data collection module is used to collect equipment status data and environmental data;

[0008] The data management system includes a data processing module and a data transmission module. The data processing module pre-processes and analyzes the data information collected by the data collection module, extracts its key features, normalizes the data and establishes a data processing model;

[0009] The data transmission module is used to connect the physical entity system and the virtual digital system to realize information transmission and exchange between the physical entity system and the virtual digital system;

[0010] The virtual digital system includes a digital mapping module; the data mapping module is used to integrate the data of the data transmission module and construct a digital twin model.

[0011] Preferably, the physical entity of the floating photovoltaic power station includes a floating structure, a photovoltaic power generation system, an electrical system, and an anchoring and mooring system.

[0012] Preferably, the equipment status data includes the operating status output power, voltage and current of the photovoltaic panels; the structural health monitoring data includes the stress, strain, displacement of the floating structure and the tension, angle, length and depth of fatigue cracks of the mooring rope;

[0013] The environmental data include meteorological data that affect the operating conditions of photovoltaic panels, such as wind speed, wind direction, temperature, humidity, and air pressure; ocean data that affect the floating structure, such as wave height, wave period, tides, and ocean currents; and lighting data that affect the power generation of photovoltaic panels, such as solar radiation intensity and sunshine duration.

[0014] Preferably, the data mapping module constructs the digital twin model including:

[0015] According to the basic data of the floating photovoltaic power station physical entity, a finite element model is established; according to the sensor layout strategy and measured modal data, a test model is established.

[0016] The test model and the finite element model are subjected to geometric and modal correlation analysis, so that the test model and the finite element model are integrated to form a digital twin;

[0017] Specifically: search for vertex numbers and coordinates adjacent to the measuring points in the finite element mesh model, so that the two geometric models can be compared, matched and analyzed in the same coordinate system;

[0018] On the basis of model matching, the modal vibration correlation coefficient MAC between the modal vibration shapes of the test model and the finite element analysis model is calculated. The calculation formula of the MAC value is as follows:

[0019]

[0020] Among them, φ i and φ j are the vibration shape vectors of the i-th and j-th modes, respectively, φ i T Represents φ i The transpose of , · represents the dot product (inner product), |φ i || and |φ j || respectively represent φ i and φ j MAC is used to characterize the similarity of the modal vibration shapes between two models.

[0021] The MAC value is a scalar between 0 and 1. When the MAC value is 1, it means that the two vibration modes are completely correlated and are the same mode; when the MAC value is 0, it means that the two vibration modes are linearly independent.

[0022] When the diagonal elements of the MAC matrix are ≥70% and the off-diagonal elements are ≤10%, it can be considered that the correlation between the two models meets the criteria;

[0023] The fused test model and finite element model combine the experimental data and the finite element simulation data, and the goal of the fusion is to correct the finite element model through the test data.

[0024] Preferably, the virtual digital system further comprises an analysis and processing module, which is used to analyze and process the physical entity state of the floating photovoltaic power station in combination with the monitored physical entity data and environmental data, and establish an integrated coupling simulation model of pneumatic-hydrodynamic-structural mechanics to predict and evaluate the behavior and performance of the floating photovoltaic power station under different environmental conditions;

[0025] The aerodynamic analysis uses the Navier-Stokes equation to describe the fluid flow. For incompressible airflow, the basic equation is:

[0026]

[0027] Where ρ is the fluid density, v is the velocity field, p is the pressure, μ is the fluid viscosity coefficient, and f ext As an external force, wind load is usually calculated by wind pressure, which can be obtained by the aerodynamic pressure formula:

[0028]

[0029] Where ρ is air density, v is wind speed, C d is the drag coefficient, A is the frontal area;

[0030] Hydrodynamic analysis also uses the Navier-Stokes equations to describe fluid flow. For incompressible water flow, the basic equation is:

[0031]

[0032] Where ρ is the fluid density, v is the velocity field, p is the pressure, μ is the fluid viscosity coefficient, and f ext is the external force, f hydro It is the force caused by hydrodynamics;

[0033] When a floating platform is subjected to wave action, the Morison equation is used to calculate the hydrodynamic force:

[0034]

[0035] Where ρ is the density of water, C d is the drag coefficient, A is the exposed area above water, v is the water velocity, and v f is the structural velocity, C m is the mass resistance coefficient, V is the volume of the object, is the water flow acceleration;

[0036] The structural mechanics model adopts finite element analysis, and its equilibrium equation is:

[0037]

[0038] Where M is the mass matrix of the structure, C is the damping matrix, K is the stiffness matrix, u is the displacement vector of the structure, and F ext is the external load, the response of the structure, obtained by solving the above equilibrium equations, and the stress-strain relationship of the structure using Hooke's law:

[0039] σ=Eε

[0040] In the formula, σ is stress, E is elastic modulus, and ε is strain;

[0041] After independently solving aerodynamics, hydrodynamics and structural mechanics, the results are iteratively exchanged and a coupled calculation method is adopted. The coupling process first performs aerodynamic calculations to obtain aerodynamic loads. After the aerodynamic loads are transferred to the structural mechanics model, a structural response analysis is performed. The hydrodynamic model is updated according to the structural response, and hydrodynamic calculations are performed. Then, the influence of water flow on the structure is obtained, and finally the iterative process is performed until convergence.

[0042] Preferably, the virtual digital system further comprises a danger warning module, and the danger warning module is used to issue warning information according to the result of the analysis and processing module.

[0043] The present invention provides a digital twin monitoring method for an offshore floating photovoltaic power station, comprising the following steps:

[0044] 1) Acquiring relevant data based on a data collection module, wherein the relevant data includes meteorological data, ocean data, light data, and equipment status data;

[0045] 2) constructing a three-dimensional model based on the relevant data collected in step 1) to synchronize it with the entity;

[0046] 3) Using the virtual digital system to accept relevant data finite element analysis software to automatically perform parametric modeling to generate a finite element crack model;

[0047] 4) Apply stress by loading the wind and wave load stress data recorded by the sensor and perform finite element analysis on the crack model;

[0048] 5) Summarize the analysis results and feed them back to the virtual model database for data visualization.

[0049] An electronic device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned digital twin monitoring method for an offshore floating photovoltaic power station when executing the program.

[0050] A non-transitory computer-readable storage medium is also provided, on which a computer program is stored, characterized in that when the computer program is executed by a processor, the steps of the above-mentioned digital twin monitoring method for an offshore floating photovoltaic power station are implemented.

[0051] Compared with the prior art, the present invention has the following beneficial technical effects:

[0052] The offshore floating photovoltaic monitoring digital twin system of the present invention can not only improve the efficiency and reliability of photovoltaic power generation through intelligent and digital technology, but also enhance the early warning capability of marine weather changes, providing new ideas and methods for the development of marine renewable energy. Specifically, a three-dimensional model is constructed through the collected relevant data to synchronize it with the entity; a virtual digital system is used to accept relevant data finite element analysis software to automatically perform parametric modeling to generate a finite element crack model; stress is applied by loading stress data of wind and wave loads recorded by sensors and finite element analysis is performed on the crack model; the analysis results are summarized and fed back to the virtual model database for data visualization. It is convenient to predict the status of the equipment according to environmental factors. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 Schematic diagram of the system architecture of a digital twin monitoring system for an offshore floating photovoltaic power station in an embodiment of the present invention;

[0054] Figure 2 A schematic diagram of data collection of a physical entity system in an embodiment of the present invention;

[0055] Figure 3 This is a flowchart of the virtual digital system in an embodiment of the present invention;

[0056] Figure 4 is a flowchart of fatigue analysis in an embodiment of the present invention;

[0057] Figure 5 This is a schematic diagram of the operation of the danger warning module in an embodiment of the present invention;

[0058] Figure 6 This is a flow chart of a digital twin monitoring method for an offshore floating photovoltaic power station in an embodiment of the present invention;

[0059] Figure 71 is a structural block diagram of an electronic device in an embodiment of the present invention. DETAILED DESCRIPTION

[0060] In order to make the purpose, technical solution and advantages of the embodiment of the present invention clearer, the technical solution of the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings of the embodiment of the present invention. Obviously, the described embodiment is a part of the embodiment of the present invention, not all of the embodiments. Based on the described embodiment 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.

[0061] The terms "comprises", "includes", "having" and any variations thereof as used in this application are intended to cover non-exclusive inclusions; for example, a process, method, system, product or apparatus comprising a series of steps or modules (units) is not limited to the listed steps or modules (units), but may include unlisted steps or modules (units), or may include other steps or modules (units) inherent to these processes, methods, products or apparatuses.

[0062] See also Figure 1 , the present invention provides a digital twin monitoring system for an offshore floating photovoltaic power station, including a physical entity system, a data management system and a virtual digital system;

[0063] The physical entity system includes a floating photovoltaic power station physical entity and a data collection module, and the data collection module is used to collect equipment status data and environmental data;

[0064] In this embodiment, the physical entity of the floating photovoltaic power station includes a floating structure, a photovoltaic power generation system, an electrical system, and an anchoring and mooring system. It is a device that generates electricity on the ocean by connecting photovoltaic module inverters and other power generation equipment through a floating body and an anchoring system. The specific structure and working principle will not be described in detail.

[0065] In this embodiment, the data collection module uses various sensors configured on the physical entity of the floating photovoltaic power station to monitor the environmental data and motion response changes. For example, the temperature and humidity sensor displays temperature and humidity information data, and the tension sensor displays cable force change information. Through the MODBUS / TCP protocol, the system uses communication technology to transmit the above sensor collected data to the data management system. The various data transmitted in real time will ensure that the physical entity motion changes are consistent with the digital twin motion changes, thereby ensuring the accuracy and timeliness of the analysis and processing results.

[0066] In this embodiment, the equipment status data includes the operating status output power, voltage, and current of the photovoltaic panel; the structural health monitoring data includes the stress, strain, displacement of the floating structure and the tension, angle, and length and depth of fatigue cracks of the mooring rope;

[0067] In this embodiment, the environmental data includes meteorological data that affect the operating conditions of photovoltaic panels, such as wind speed, wind direction, temperature, humidity, and air pressure; ocean data that affect the floating structure, such as wave height, wave period, tides, and ocean currents; and lighting data that affect the power generation of photovoltaic panels, such as solar radiation intensity and sunshine duration.

[0068] Among them, data such as power generation information is used for managers to understand the working efficiency and usage time of the power station; meteorological data and ocean data are used to display the working environment of the power station and provide data support for analyzing its motion response; equipment status data is used to analyze the health status of the power station, including the expansion of cracks and the remaining service life.

[0069] The data management system includes a data processing module and a data transmission module. The data processing module generates a virtual model based on the collected data information, which contains various types of data information after normalization management. The specific execution steps are as follows:

[0070] Use 3DMax and other 3D modeling software to create a 1:1 virtual digital model of the physical entity, and also integrate environmental information such as Figure 2 Data management and update. This includes meteorological data such as wind speed, wind direction, temperature, humidity, and air pressure to evaluate the operating conditions and performance of photovoltaic panels; ocean data such as wave height, wave period, tide, and ocean current to understand and predict the dynamic response of floating structures; and light data such as solar radiation intensity and sunshine duration that directly affect the power generation of photovoltaic panels. In addition to environmental data, it also includes the operating status output power, voltage, and current of photovoltaic panels, structural health monitoring data, and equipment status data such as stress, strain, displacement, tension and angle of mooring ropes, length and depth of fatigue cracks of floating structures. This is a conventional technology, and the specific steps will not be repeated.

[0071] Classify and manage various data information. The data transmission module is used to connect the physical entity system and the virtual digital system to realize the transmission and exchange of information between the physical entity system and the virtual digital system; for example, transmission is carried out through a wireless network or an optical fiber transmission network. This is a conventional technology and the specific steps will not be repeated here.

[0072] The data management system transmits the processed information and model to the virtual digital system through the data transmission module. The virtual digital system further processes and analyzes based on the finite element model. The conversion between the virtual model and the finite element model is an existing technology and will not be described in detail. The data such as the structural stress of the photovoltaic system and the fatigue damage of key nodes are obtained. Figure 3As shown, in order to ensure that the calculated defect-related information can be intuitively understood and used by management and maintenance personnel, the system adopts a graphical data presentation method. Specifically, the system will convert the collected and analyzed data information into pictures and charts and display them on the user interface. By using pictures and charts, complex structural analysis results are converted into easy-to-understand visual information, which greatly enhances the accessibility of data and the convenience of decision makers. When the defect data reaches the critical value of danger, the system will autonomously issue a forecast warning to ensure the safety of its working process, thus providing an efficient tool for structural integrity management and long-term performance monitoring.

[0073] The virtual digital system performs the following steps:

[0074] The digital mapping module will synchronize the changes of the physical entity and the digital twin, that is, first update the virtual digital model, update the changes in the data information indicated by each sensor, and use the unity engine to establish a visualization model for the updated information. Through virtual reality technology, the working status of the physical entity is intuitively displayed to achieve seamless data interaction. For example, managers can immersively experience the working environment and work efficiency of the offshore floating photovoltaic power station through VR roaming and other methods.

[0075] In this embodiment, the virtual digital system includes a digital mapping module; the data mapping module is used to integrate the data of the data transmission module and construct a digital twin model.

[0076] In this embodiment, the data mapping module constructs a digital twin model including:

[0077] According to the basic data of the physical entity of the floating photovoltaic power station, a finite element model is established; according to the sensor layout strategy and the measured modal data, a test model is established; the establishment of the finite element model and the test model is a conventional technology, and the specific steps are not repeated here.

[0078] The test model and the finite element model are subjected to geometric and modal correlation analysis, so that the test model and the finite element model are integrated to form a digital twin;

[0079] Specifically: search for vertex numbers and coordinates adjacent to the measuring points in the finite element mesh model, so that the two geometric models can be compared, matched and analyzed in the same coordinate system;

[0080] The test model and the finite element model are subjected to geometric and modal correlation analysis to fuse the test model and the finite element model to form a digital twin; the geometric correlation analysis aligns the test geometric model and the finite element mesh model through coordinate transformation methods such as rotation and scaling;

[0081] This step searches for vertex numbers and coordinates close to the measuring points in the finite element mesh model through least squares, geometric topology and other algorithms, so that the two geometric models can be compared, matched and analyzed in the same coordinate system, ensuring that the finite element model can accurately reflect the geometric characteristics of the experimental model;

[0082] On the basis of model matching, the modal vibration correlation coefficient MAC between the modal vibration shapes of the test model and the finite element analysis model is calculated. The calculation formula of the MAC value is as follows:

[0083]

[0084] Among them, φ i and φ j are the vibration shape vectors of the i-th and j-th modes, respectively, φ i T Represents φ i The transpose of , · represents the dot product (inner product), |φ i || and |φ j || respectively represent φ i and φ j MAC is used to characterize the similarity of the modal vibration shapes between two models.

[0085] The MAC value is a scalar between 0 and 1. When the MAC value is 1, it means that the two vibration modes are completely correlated and are the same mode; when the MAC value is 0, it means that the two vibration modes are linearly independent.

[0086] When the diagonal elements of the MAC matrix are ≥70% and the non-diagonal elements are ≤10%, it can be considered that the correlation between the two models meets the criteria; that is, calculate several MAC values ​​to form a MAC matrix, and then determine whether the matrix meets the conditions.

[0087] The fusion test model and finite element model combine experimental data and finite element simulation data. The goal of the fusion is to correct the finite element model through test data. Experimental data is used to improve the parameters of the simulation model, thereby improving the overall accuracy and credibility of the model. The model can simulate physical entity changes more accurately.

[0088] It is also possible to achieve reverse control and optimization of the digital twin over the physical entity. The physical entity transmits the damage situation to the numerical twin through sensors. After finite element analysis, if the latter concludes that the structure is about to be damaged, it will issue an alarm to remind the operation and maintenance personnel to carry out maintenance in time. If necessary, the offshore operation of the physical entity can be stopped immediately to ensure safety. This two-way mapping ensures real-time synchronization and interaction between the physical entity and the digital twin.

[0089] In this embodiment, the virtual digital system also includes an analysis and processing module, which is used to analyze and process the physical entity state of the floating photovoltaic power station in combination with the monitored physical entity data and environmental data, and establish an integrated coupling simulation model of pneumatic-hydrodynamic-structural mechanics to provide the behavior performance of the physical entity of the floating photovoltaic power station in different environments. The integrated coupling simulation model of pneumatic-hydrodynamic-structural mechanics simulates the response of the floating photovoltaic power station in the actual environment by comprehensively considering the interaction of wind (pneumatics), water movement (waves, currents, etc.) and structural mechanics (platforms, brackets, photovoltaic modules, etc.). This integrated coupling model can not only more accurately evaluate the performance of the floating photovoltaic power station under different environmental conditions, but also provide reliable data support for optimized design and long-term operation.

[0090] The aerodynamic-hydrodynamic-structural mechanics integrated coupling simulation model is used to simulate and analyze complex multi-physics problems involving aerodynamics, hydrodynamics and structural response. Such multi-physics coupling problems usually require joint solutions combining mechanical principles and equations from different disciplines.

[0091] The aerodynamic analysis uses the Navier-Stokes equation to describe the fluid flow. For incompressible airflow, the basic equation is:

[0092]

[0093] Where ρ is the fluid density, v is the velocity field, p is the pressure, μ is the fluid viscosity coefficient, and f ext As an external force, wind load is usually calculated by wind pressure, which can be obtained by the aerodynamic pressure formula:

[0094]

[0095] Where ρ is air density, v is wind speed, C d is the drag coefficient, A is the frontal area;

[0096] Hydrodynamic analysis also uses the Navier-Stokes equations to describe fluid flow. For incompressible water flow, the basic equation is:

[0097]

[0098] Where ρ is the fluid density, v is the velocity field, p is the pressure, μ is the fluid viscosity coefficient, and f ext is the external force, f hydro It is the force caused by hydrodynamics;

[0099] When a floating platform is subjected to wave action, the Morison equation is used to calculate the hydrodynamic force:

[0100]

[0101] Where ρ is the density of water, C d is the drag coefficient, A is the exposed area above water, v is the water velocity, and v f is the structural velocity, C m is the mass drag coefficient, V is the volume of the object, is the water flow acceleration;

[0102] The structural mechanics model adopts finite element analysis, and its equilibrium equation is:

[0103]

[0104] Where M is the mass matrix of the structure, C is the damping matrix, K is the stiffness matrix, u is the displacement vector of the structure, and F ext is the external load, the response of the structure, obtained by solving the above equilibrium equations, and the stress-strain relationship of the structure using Hooke's law:

[0105] σ=Eε

[0106] In the formula, σ is stress, E is elastic modulus, and ε is strain;

[0107] After aerodynamics, hydrodynamics and structural mechanics are solved independently, the results are iteratively exchanged and a coupled calculation method is adopted. In the coupling process, aerodynamic calculations are first performed to obtain aerodynamic loads. After the aerodynamic loads are transferred to the structural mechanics model, a structural response analysis is performed. The hydrodynamic model is updated according to the structural response, and hydrodynamic calculations are performed. Then, the influence of water flow on the structure is obtained, and the iterative process is finally carried out until convergence.

[0108] The analysis and processing module analyzes and processes the structural status of the floating photovoltaic power station by combining monitoring physical entities and environmental data. By establishing an accurate finite element numerical model, it can predict and evaluate the behavior and performance of the floating photovoltaic power station under different environmental conditions. Based on the evaluation of the ultimate strength and fatigue strength of the photovoltaic system structure, it provides a comprehensive safety analysis for the photovoltaic power station and provides a theoretical basis and conditions for engineers to conduct further analysis and decision-making.

[0109] In addition to showing real-time changes in physical entities, virtual digital systems can also provide deeper analysis and prediction, such as fatigue cracks in its structure. Figure 4After receiving the information, the virtual digital system uses finite element analysis software such as ANSYS to automatically perform parametric modeling to generate a crack finite element model, and applies stress by loading the wind and wave load stress data recorded by the sensor. Subsequently, the system performs finite element analysis on the crack model and summarizes the analysis results, such as the structural ultimate strength and fatigue life data. The above results are fed back to the virtual model database for data visualization. In the fatigue analysis process, this paper uses the fracture mechanics method to calculate fatigue damage extension. The fracture mechanics method describes the crack extension process based on parameters such as the stress field intensity factor at the crack tip, which can provide more accurate crack extension rate and residual life prediction. This paper takes the most common opening type as an example to study the impact of cracks on the structure. When calculating the crack extension life of the structure, the load and fatigue crack extension rate of the structure are crucial. Paris believes that the stress intensity factor can not only represent the stress field intensity at the crack tip but also is an important factor in promoting crack extension. Therefore, the formula for expressing the crack extension law is proposed as follows, which is the most widely used crack extension model in fatigue crack extension analysis.

[0110]

[0111] Where c and m are material constants related to the test conditions (environment, frequency, temperature, stress, etc.), a is the crack depth, N is the number of stress cycles, and ΔK is the amplitude of the stress intensity factor.

[0112] In this embodiment, the virtual digital system further includes a danger warning module, which is used to issue warning information according to the results of the analysis and processing module.

[0113] Based on the results of the data analysis module, such as the structural ultimate strength and fatigue strength of the photovoltaic system, the hazard warning module evaluates the safety of equipment operation of offshore floating photovoltaic power plants when facing risk conditions, including equipment failure, structural damage, etc. This assessment helps to determine which risks require immediate attention and response. Once potential risks are identified, the system will issue an early warning to notify operation and maintenance personnel to take necessary preventive or mitigation measures. These warnings can be automatic or manually triggered based on preset conditions. Through early warning and response, the hazard warning module significantly improves the safety and operation and maintenance efficiency of offshore floating photovoltaic power plants and reduces potential losses and risks.

[0114] Specifically, after completing the in-depth analysis of the physical entity system data, the hazard warning module will evaluate it. When it is determined that its structural performance is sufficient and not enough to cause danger to the structure, the digital mapping module will update the analysis data and display it to the manager intuitively in the form of charts and other methods. At the same time, when the hazard warning module determines that its structural performance is sufficient to cause danger, such as when the structural strength is lower than the safety setting value, or when the service life is insufficient due to fatigue, etc., there is a potential risk caused by the above situation. The system hazard warning module will issue an early warning to notify the operation and maintenance personnel to take necessary preventive or mitigation measures. These warnings can be automatic or manually triggered based on preset conditions. Figure 5 As shown in the figure, in addition to the danger information calculated by the virtual digital system, errors in power generation calculation and abnormal display of sensor data can all be used as preconditions for triggering the crisis warning of the danger warning module. Furthermore, the virtual digital system can also synchronize satellite information to display the synchronized location information of disaster weather such as tsunamis and typhoons, so as to take measures in advance to avoid impacts and losses.

[0115] See also Figure 6 This embodiment provides a digital twin monitoring method for an offshore floating photovoltaic power station, comprising the following steps:

[0116] 1) Obtain relevant data based on the data collection module, including meteorological data, ocean data, light data and equipment status data;

[0117] 2) constructing a three-dimensional model based on the relevant data collected in step 1) to synchronize it with the entity;

[0118] 3) Using the virtual digital system to accept relevant data finite element analysis software to automatically perform parametric modeling to generate a finite element crack model;

[0119] 4) Apply stress by loading the wind and wave load stress data recorded by the sensor and perform finite element analysis on the crack model;

[0120] 5) Summarize the analysis results and feed them back to the virtual model database for data visualization.

[0121] See also Figure 7 , a structural block diagram of an electronic device provided by an embodiment of the present invention, such as Figure 7 As shown, the electronic device may include: a processor 610, a communication interface 620, a memory 630 and a communication bus 640, wherein the processor 610, the communication interface 620 and the memory 630 communicate with each other through the communication bus 640. The processor 610 may call the logic instructions in the memory 630 to execute the following method:

[0122] Acquire relevant data based on the data collection module, wherein the relevant data includes meteorological data, ocean data, light data and equipment status data;

[0123] Build a 3D model based on the collected relevant data and synchronize it with the entity;

[0124] Utilize the virtual digital system to accept relevant data and finite element analysis software to automatically perform parametric modeling and generate a finite element crack model;

[0125] Stress was applied by loading stress data of wind and wave loads recorded by sensors and finite element analysis was performed on the crack model;

[0126] Summarize the analysis results and feed them back to the virtual model database for data visualization.

[0127] In addition, the logic instructions in the above-mentioned memory 630 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0128] An embodiment of the present invention further provides a non-transitory computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the method provided in each of the above embodiments is implemented, for example, including:

[0129] Acquire relevant data based on the data collection module, wherein the relevant data includes meteorological data, ocean data, light data and equipment status data;

[0130] Build a 3D model based on the collected relevant data and synchronize it with the entity;

[0131] Utilize the virtual digital system to accept relevant data and finite element analysis software to automatically perform parametric modeling and generate a finite element crack model;

[0132] Stress was applied by loading stress data of wind and wave loads recorded by sensors and finite element analysis was performed on the crack model;

[0133] Summarize the analysis results and feed them back to the virtual model database for data visualization.

[0134] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods of each embodiment or some parts of the embodiment.

[0135] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A digital twin monitoring system for an offshore floating photovoltaic power station, characterized in that: Includes physical entity systems, data management systems and virtual digital systems; The physical entity system includes a floating photovoltaic power station physical entity and a data collection module, wherein the data collection module is used to collect equipment status data and environmental data; The data management system includes a data processing module and a data transmission module. The data processing module pre-processes and analyzes the data information collected by the data collection module, extracts its key features, normalizes the data and establishes a data processing model; The data transmission module is used to connect the physical entity system and the virtual digital system to realize information transmission and exchange between the physical entity system and the virtual digital system; The virtual digital system includes a digital mapping module; the data mapping module is used to integrate the data of the data transmission module and construct a digital twin model.

2. According to claim 1, a digital twin monitoring system for an offshore floating photovoltaic power station is characterized in that: The physical entity of the floating photovoltaic power station includes a floating structure, a photovoltaic power generation system, an electrical system, and an anchoring and mooring system.

3. According to claim 1, a digital twin monitoring system for an offshore floating photovoltaic power station is characterized in that: The equipment status data includes the operating status output power, voltage and current of the photovoltaic panels; the structural health monitoring data includes the stress, strain, displacement of the floating structure and the tension, angle, length and depth of fatigue cracks of the mooring rope; The environmental data include meteorological data that affect the operating conditions of photovoltaic panels, such as wind speed, wind direction, temperature, humidity, and air pressure; ocean data that affect the floating structure, such as wave height, wave period, tides, and ocean currents; and lighting data that affect the power generation of photovoltaic panels, such as solar radiation intensity and sunshine duration.

4. According to claim 1, a digital twin monitoring system for an offshore floating photovoltaic power station is characterized in that: The data mapping module constructs a digital twin model including: According to the basic data of the floating photovoltaic power station physical entity, a finite element model is established; according to the sensor layout strategy and measured modal data, a test model is established. The test model and the finite element model are subjected to geometric and modal correlation analysis, so that the test model and the finite element model are integrated to form a digital twin; Specifically: search for vertex numbers and coordinates adjacent to the measuring points in the finite element mesh model, so that the two geometric models can be compared, matched and analyzed in the same coordinate system; On the basis of model matching, the modal vibration correlation coefficient MAC between the modal vibration shapes of the test model and the finite element analysis model is calculated. The calculation formula of the MAC value is as follows: Among them, φ i and φ j are the vibration shape vectors of the i-th and j-th modes respectively, Represents φ i The transpose of , which represents the dot product, ||φ i || and ||φ j || respectively represent φ i and φ j MAC is used to characterize the similarity of the modal vibration shapes between two models. The MAC value is a scalar between 0 and 1. When the MAC value is 1, it means that the two vibration modes are completely correlated and are the same mode; when the MAC value is 0, it means that the two vibration modes are linearly independent. When the diagonal elements of the MAC matrix are ≥70% and the off-diagonal elements are ≤10%, it can be considered that the correlation between the two models meets the criteria.

5. The digital twin monitoring system for an offshore floating photovoltaic power station according to claim 1, characterized in that: The virtual digital system further comprises an analysis and processing module, which is used to analyze and process the physical entity state of the floating photovoltaic power station in combination with the monitored physical entity data and environmental data, and to establish an integrated coupling simulation model of pneumatic-hydrodynamic-structural mechanics; The aerodynamic analysis uses the Navier-Stokes equation to describe the fluid flow. For incompressible airflow, the basic equation is: Where ρ is the fluid density, v is the velocity field, p is the pressure, μ is the fluid viscosity coefficient, and f ext As an external force, wind load is usually calculated by wind pressure, which can be obtained by the aerodynamic pressure formula: In the formula, ρ is air density, v is wind speed, C d is the drag coefficient, A is the windward area; Hydrodynamic analysis also uses the Navier-Stokes equations to describe fluid flow. For incompressible water flow, the basic equation is: Where ρ is the fluid density, v is the velocity field, p is the pressure, μ is the fluid viscosity coefficient, and f ext is the external force, f hydro It is the force caused by hydrodynamics; When a floating platform is subjected to wave action, the Morison equation is used to calculate the hydrodynamic force: Where ρ is the density of water, C d is the drag coefficient, A is the exposed area above water, v is the water velocity, and v f is the structural velocity, C m is the mass drag coefficient, V is the volume of the object, is the water flow acceleration; The structural mechanics model adopts finite element analysis, and its equilibrium equation is: Where M is the mass matrix of the structure, C is the damping matrix, K is the stiffness matrix, u is the displacement vector of the structure, and F ext is the external load, the response of the structure, obtained by solving the above equilibrium equations, and the stress-strain relationship of the structure using Hooke's law: σ=Eε In the formula, σ is stress, E is elastic modulus, and ε is strain; After independently solving aerodynamics, hydrodynamics and structural mechanics, the results are iteratively exchanged and a coupled calculation method is adopted. The coupling process first performs aerodynamic calculations to obtain aerodynamic loads. After the aerodynamic loads are transferred to the structural mechanics model, a structural response analysis is performed. The hydrodynamic model is updated according to the structural response, and hydrodynamic calculations are performed. Then, the influence of water flow on the structure is obtained, and finally the iterative process is performed until convergence.

6. The digital twin monitoring system for an offshore floating photovoltaic power station according to claim 1, characterized in that: The virtual digital system further comprises a danger warning module, and the danger warning module is used to issue warning information according to the result of the analysis and processing module.

7. A digital twin monitoring method for an offshore floating photovoltaic power station, characterized in that: The steps include: 1) Acquiring relevant data based on a data collection module, wherein the relevant data includes meteorological data, ocean data, light data, and equipment status data; 2) constructing a three-dimensional model based on the relevant data collected in step 1) to synchronize it with the entity; 3) Using the virtual digital system to accept relevant data finite element analysis software to automatically perform parametric modeling to generate a finite element crack model; 4) Apply stress by loading the wind and wave load stress data recorded by the sensor and perform finite element analysis on the crack model; 5) Summarize the analysis results and feed them back to the virtual model database for data visualization.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the digital twin monitoring method for an offshore floating photovoltaic power station as described in claim 7 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the digital twin monitoring method for an offshore floating photovoltaic power station as described in claim 7 are implemented.

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