A real-time monitoring and intelligent control system for floating wind turbines based on digital twins and environmental testing

Abstract

This invention discloses a real-time monitoring and intelligent control system for floating wind turbines based on digital twins and environmental testing. The system comprises an on-site monitoring system with modules for detecting wind turbine status and sea conditions; a digital twin system with modules for real-time monitoring, environmental prediction, intelligent testing, and feedback control; and an environmental simulation system with a laboratory-scale model of the wind turbine, environmental simulation equipment, and measurement equipment. The floating wind turbine is equipped with a liquid damper. This system integrates the complementary elements of actual physical engineering, digital modeling, and scale testing optimization for the floating wind turbine. This system can reproduce both digital and physical models of the floating wind turbine's actual operating state, providing a reliable basis for technical personnel to monitor and make decisions, thereby ensuring the longevity of the floating wind turbine.

Description

Technical Field

[0001] The present invention belongs to the technical field of offshore wind power, and specifically relates to a real-time monitoring and intelligent control system for floating wind turbines based on digital twins and environmental tests. Background Art

[0002] With the development of marine resource development technology, floating wind turbines have become one of the important equipment for deep-sea wind energy development. The deep sea has richer wind energy resources, but the wind and wave environment conditions are relatively harsh. The continuous swinging of floating wind turbines will reduce the quality of wind turbine power generation, affect the service life of wind turbines, and aggravate platform fatigue damage. Traditional wind turbine model tests often do not have wind and rain simulation devices, which cannot meet the simulation requirements of sea areas such as the South China Sea, which are often accompanied by typhoons and tropical storms. The selected wave and wind conditions are fixed and cannot be consistent with actual sea conditions. In addition, in the face of complex broadband wind and wave load excitation, there is a lack of an intelligent control system that integrates real-time detection, forecasting, and control.

[0003] Existing wind turbine design processes typically involve building a wind turbine model in a test tank, ensuring that the turbine's ultimate load and motion amplitude meet design standards under extreme sea conditions, before construction and installation. This results in a one-way process, preventing data feedback from the wind turbine platform in the actual marine environment. Conventional digital twin technology, after acquiring information on wind turbine motion and load, is unable to implement an optimal control strategy for the structure. Therefore, there is an urgent need to establish an environmental monitoring and intelligent control system based on digital twin and machine learning technologies, integrating practical physical engineering, digital models, and scaled test optimization. Summary of the Invention

[0004] The purpose of the present invention is to overcome the defects of the existing technology and provide a real-time monitoring and intelligent control system for floating wind turbines based on digital twins and environmental tests. It can enable onshore technicians to monitor the operating status of offshore floating wind turbines throughout the entire process and adopt optimized control schemes to control the movement of the floating body in real time, which can effectively improve the power generation efficiency of wind turbines, reduce fatigue damage, and ensure the service life of floating wind turbines.

[0005] In order to achieve the above objectives, the present invention adopts the following technical solutions.

[0006] A real-time monitoring and intelligent control system for floating wind turbines based on digital twins and environmental testing, including an on-site detection system, a digital twin system, and an environmental simulation system. The floating wind turbine is equipped with a liquid damper and a cable tractor.

[0007] The on-site detection system is used to monitor the movement, mooring system, structural stress, wave conditions and wind force level of the floating wind turbine in actual working environment. It includes a wind turbine status detection module with a six-component instrument, a tension sensor and a strain gauge, and a sea condition environment detection module with a wave height meter, an anemometer, a rain gauge and a current meter.

[0008] The digital twin system, which includes a real-time monitoring module, an environmental prediction module, an intelligent testing module, and a feedback control module, provides a real-time three-dimensional representation of the floating wind turbine. The turbine's motion response, mooring system, structural stress and strain, and environmental conditions such as wind, waves, and rain can all be visually displayed, facilitating decision-making.

[0009] The environmental simulation test system includes a scaled-down wind turbine model and measuring equipment in the laboratory. The scaled-down wind turbine model is fixed in water by cables, and the measuring equipment is consistent with the on-site environment, including a six-component instrument, a tension sensor, a strain gauge, a wave height meter, an anemometer, a rain gauge, and a current meter. After the scaled-down wind turbine model is installed, the floating wind turbine real-time monitoring and intelligent control system simulates the on-site wind, rain, and wave flow environment by adjusting the wave-making plate, blower, rainmaker, water suction pump, and water extraction pump. All measured data is summarized to the calculator through the data integrator, and the parameters are corrected by the intelligent system to keep it similar to the on-site environment, thereby realizing the dual reproduction of the digital and physical models of the actual operating status of the on-site floating wind turbine.

[0010] Specifically, the on-site monitoring system's wind turbine status detection module uses a six-component instrument to obtain wind turbine displacement and rotation data, a tension sensor to obtain mooring force data, and a strain gauge to obtain local position strain. The sea condition and environmental monitoring module uses a wave height meter to obtain wave parameters, an anemometer to obtain wind speed and direction, a rain gauge to obtain rainfall, and a current meter to obtain flow velocity and direction. This transmits wind turbine operating status and environmental data to the digital twin system via a wireless signal station. The on-site monitoring system is powered by the wind turbine's own electricity generation, with solar cells as a backup power source.

[0011] Specifically, the digital twin system, its real-time monitoring module constructs a three-dimensional structure and environmental digital model of the on-site floating wind turbine, which facilitates intuitive understanding of the on-site wind turbine status and surrounding environment; the environmental prediction module uses machine learning technology to predict wind, wave, current and sea conditions in the future based on on-site wind and wave data, and uses this information as input conditions for model tests; the intelligent test module is controlled by an intelligent system, and the system continuously learns and adjusts the liquid level in the liquid damper and the length of the cable tractor through test data to obtain the optimal solution for wind turbine vibration reduction control; the feedback control module feeds back the parameters of the liquid damper and cable tractor to the site through a wireless signal station to achieve the best control solution.

[0012] Specifically, the wind, rain, and wave flow parameters generated by the intelligent test module of the digital twin system are fed back to the calculator in real time through the wave height meter, anemometer, rain gauge, and current meter. The wave parameters are controlled by adjusting the movement of the wave-making plate. The relationship is as follows: Where H is the wave height, S is the stroke of the wave-making plate, k is the wave-making plate and wave frequency, and h is the water depth. The wind force is controlled by adjusting the blower speed. The rainfall is adjusted by adjusting the water pressure of the rainmaker. The flow rate and direction are adjusted by adjusting the power and distribution position of the suction pump and the suction pump. A wave-breaking area is set downstream of the pool to reduce the impact of backflow and improve the test accuracy.

[0013] Specifically, the liquid damper is equipped with a wave height meter and a bidirectional water pump to adjust the liquid level of the liquid damper so that the natural frequency of the liquid damper is consistent with the shaking frequency of the floating wind turbine to achieve the best damping effect; the natural frequency ω0 of the liquid damper is expressed as: Where A v and A h are the cross-sectional areas of the vertical and horizontal pipes of the U-shaped pipe, L v and L h are the lengths of the vertical and horizontal liquid columns in the TLMCD at the initial moment, respectively, and g is the acceleration due to gravity.

[0014] Specifically, the cable tractor adjusts the cable length under the control of the intelligent system, continuously self-trains to obtain the optimal cable length under current sea conditions, and provides a restoring torque to the floating wind turbine to ensure the stability of the wind turbine platform.

[0015] Furthermore, the wave-making plate of the environmental simulation test system adjusts the wave direction and wind direction angle through a rotating device, the blower controls the wind direction angle and height through a crane, and adjusts the flow direction by starting the water suction pump and the water extraction pump at different positions.

[0016] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0017] The present invention provides a real-time monitoring and intelligent control system for floating wind turbines based on digital twins and environmental tests. The digital twin technology is used to digitize the working status of the floating wind turbine, monitor the operating status of the floating wind turbine at any time, and reduce the operation and maintenance costs. The environmental simulation is used to scale the sea conditions in which the wind turbine is located, so that technical personnel can more intuitively understand the environment in which the wind turbine is located under different climatic conditions, thereby improving the reliability of commercial operation planning. The environmental prediction module uses machine learning to predict sea conditions in the future, to warn against possible extreme wind and wave effects, and to enable the wind turbine to enter survival mode in advance to avoid damage. The intelligent test module automatically adjusts the wind and wave parameters for testing, and uses the predicted wind and wave conditions to continuously carry out training and learning to obtain the optimized damper parameters and cable control scheme, thereby significantly saving labor costs. After the optimized parameters are fed back to the site, more effective vibration control of the floating wind turbine is achieved, ensuring the safety of the mooring system and the service life of the floating wind turbine. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is an overall schematic diagram of an environmental simulation system according to an embodiment of the present invention.

[0019] Figure 2 It is a schematic top view of an environmental simulation system according to an embodiment of the present invention.

[0020] Figure 3 It is a schematic diagram of the interior of a scaled model of a wind turbine according to an embodiment of the present invention.

[0021] Figure 4 It is a structural schematic diagram of a real-time monitoring and intelligent control system for floating wind turbines based on digital twins and environmental tests of the present invention.

[0022] In the figure, 1- six-component instrument, 2- tension sensor, 3- strain gauge, 4- wave height meter, 5- anemometer, 6- rain gauge, 7- current meter, 8- wireless signal station, 9- liquid damper, 10- cable tractor, 11- wave maker, 12- blower, 13- rainmaker, 14- water suction pump, 15- water extraction pump, 16- scale model of wind turbine, 17- calculator, 18- bidirectional water pump, 19- data integrator, 20- cable. DETAILED DESCRIPTION

[0023] The present invention will be described in further detail below with reference to the accompanying drawings.

[0024] like Figure 4 The figure shows a real-time monitoring and intelligent control system for a floating wind turbine based on digital twins and environmental testing. The system includes an on-site detection system, a digital twin system, and an environmental simulation system. This system reproduces both the digital and physical models of the floating wind turbine's actual operating state. The floating wind turbine is equipped with a liquid damper 9 and a cable tractor 10.

[0025] The on-site monitoring system is geometrically similar to the scaled-down model of the wind turbine in the laboratory, and the arrangement of measuring instruments remains consistent. It monitors the floating wind turbine's motion, mooring system, structural stress, wave conditions, and wind force levels under actual operating conditions. It includes a turbine status monitoring module equipped with a six-component instrument, a tension sensor, and strain gauges, and a sea-condition monitoring module equipped with a wave height meter, anemometer, rain gauge, and current meter. The turbine status monitoring module uses the six-component instrument to obtain turbine displacement and rotation data, the tension sensor to obtain mooring force data, and the strain gauge to obtain local strain. The sea-condition monitoring module uses a wave height meter to obtain wave parameters, an anemometer to obtain wind speed and direction, a rain gauge to obtain rainfall, and a current meter to obtain flow velocity and direction. This data is then transmitted to the digital twin system via wireless signal station 8.

[0026] The on-site detection system is powered by the wind turbine itself and is equipped with solar cells as a backup power source.

[0027] The digital twin system, comprising a real-time monitoring module, an environmental prediction module, an intelligent testing module, and a feedback control module, provides a real-time, three-dimensional representation of the floating wind turbine. The turbine's motion response, mooring system, structural stress and strain, and environmental conditions such as wind, waves, and rain are all visually displayed, facilitating decision-making. The real-time monitoring module constructs a three-dimensional structural and environmental digital model of the floating wind turbine, allowing technicians to intuitively understand the turbine's status and on-site environmental conditions. The environmental prediction module uses machine learning technology to predict future sea conditions (wind, waves, and currents) based on on-site wind and wave data, and uses this information as input for model testing. The intelligent testing module's processes are fully controlled by an intelligent system, which continuously learns and adjusts the liquid level in the liquid damper 9 and the length of the cable puller 10 based on test data to obtain the optimal solution for wind turbine vibration reduction control. The feedback control module then feeds back the parameters of the liquid damper 9 and cable puller 10 to the site via a wireless signal station 8, achieving the optimal control solution.

[0028] The wind, rain and wave flow parameters generated by the intelligent test module are fed back to the calculator 17 in real time through the wave height meter 4, anemometer 5, rain gauge 6 and current meter 7. The wave parameters are controlled by adjusting the movement of the wave-making plate 11. The relationship is: Where H is the wave height, S is the stroke of the wave-making plate, k is the frequency of the wave-making plate and waves, and h is the water depth. The wind force is controlled by adjusting the speed of the blower 12. The rainfall is adjusted by adjusting the water pressure of the rainmaker 13. The flow rate and direction are adjusted by adjusting the power and distribution position of the water suction pump 14 and the water extraction pump 15. A wave-breaking area 21 is provided downstream of the pool to reduce the impact of backflow and improve the test accuracy.

[0029] like Figure 3As shown, the liquid damper 9 in the wind turbine scale model 16 is equipped with a wave height meter 4 and a bidirectional water pump 18 to adjust the liquid level of the liquid damper 9 so that the natural frequency of the liquid damper 9 is consistent with the shaking frequency of the floating wind turbine to achieve the best damping effect. The natural frequency ω0 of the damper is expressed as: Where A v and A h are the cross-sectional areas of the vertical and horizontal pipes of the “U” type pipe, L v and L h are the lengths of the vertical and horizontal liquid columns in the TLMCD at the initial moment, respectively, and g is the acceleration due to gravity.

[0030] The intelligent system controls the cable tractor 8 to adjust the cable length, continuously self-trains to obtain the optimal cable length under the current sea conditions, provides a restoring torque to the floating wind turbine, and ensures the stability of the wind turbine platform.

[0031] The intelligent control system performs real-time correction based on the data measured in the model test to ensure the test accuracy.

[0032] The intelligent system continuously learns and adjusts the liquid level in the liquid damper 9 and the length of the cable traction device 10 to obtain the optimal solution for the fan vibration reduction control.

[0033] After obtaining the optimal control strategy for platform roll reduction through the environmental simulation test system, the intelligent test module will feed it back to the on-site control system for actual roll reduction and vibration suppression of floating wind turbines. The entire process does not require human participation, and the intelligent test module can conduct round-the-clock learning and training.

[0034] The feedback control module applies the optimal solution to the actual site to achieve the best control solution.

[0035] The environmental prediction module uses a deep neural network to predict wind and wave loads within a period of time in the future, which is about 24-48 hours. The more historical wind and wave data there is, the higher the prediction accuracy.

[0036] like Figure 1 and Figure 2 As shown, the environmental simulation test system of an embodiment of the present invention includes a laboratory-scale wind turbine model 16 and related measuring equipment. The scaled wind turbine model 16 is anchored in water by a cable 20. The measuring equipment is consistent with the on-site environment, including a six-component instrument 1, a tension sensor 2, a strain gauge 3, a wave height meter 4, an anemometer 5, a rain gauge 6, and a current meter 7. After personnel install the wind turbine model, the entire test is carried out by the intelligent test module. The intelligent system simulates the on-site wind, rain, and wave flow environment by adjusting the wave generator 11, blower 12, rainmaker 13, suction pump 14, and suction pump 15. All measured data is aggregated by a data integrator 19 and transmitted to a computer 17. The intelligent system then corrects the parameters to maintain a similarity to the on-site environment.

[0037] The wave-making plate 11 adjusts the wave direction and wind direction angle through the rotating device 22, the blower 12 controls the wind direction angle and height through the crane, and adjusts the flow direction by starting the water suction pump 14 and the water extraction pump 15 at different positions.

[0038] In summary, the real-time monitoring and intelligent control system of a floating wind turbine based on digital twin and environmental testing of the present invention digitizes the working status of the floating wind turbine through digital twin technology, monitors the operating status of the floating wind turbine at any time, and reduces operation and maintenance costs; uses environmental simulation to scale the sea conditions in which the wind turbine is located, so that technical personnel can more intuitively understand the environment in which the wind turbine is located under different climatic conditions, and improve the reliability of commercial operation planning; the environmental prediction module predicts sea conditions in the future through machine learning, and serves as a warning for possible extreme wind and wave effects, so that the wind turbine enters survival mode in advance to avoid damage; the intelligent test module automatically adjusts the wind and wave parameters for testing, and uses the predicted wind and wave conditions to continuously carry out training and learning to obtain the optimized damper parameters and cable control scheme, which greatly saves labor costs; after the optimized parameters are fed back to the site, more effective vibration control of the floating wind turbine is achieved, ensuring the safety of the mooring system and the service life of the floating wind turbine.

Claims

1. A real-time monitoring and intelligent control system for floating wind turbines based on digital twins and environmental testing, characterized by: It comprises a field detection system, a digital twin system and an environmental simulation system, wherein the floating wind turbine is provided with a liquid damper (9) and a cable tractor (10); The on-site detection system is used to monitor the movement, mooring system, structural stress, wave conditions and wind force level of the floating wind turbine in actual working environment. It includes a wind turbine status detection module with a six-component instrument, a tension sensor and a strain gauge, and a sea condition environment detection module with a wave height meter, an anemometer, a rain gauge and a current meter. The digital twin system, which includes a real-time monitoring module, an environmental prediction module, an intelligent testing module, and a feedback control module, provides a real-time three-dimensional representation of the floating wind turbine. The turbine's motion response, mooring system, structural stress and strain, and environmental conditions such as wind, waves, and rain can all be visually displayed, facilitating decision-making. The environmental simulation test system includes a scaled model (16) of a wind turbine in a laboratory and measuring equipment. The scaled model (16) of the wind turbine is fixed in water by a cable (20). The measuring equipment is consistent with the on-site environment and includes a six-component instrument (1), a tension sensor (2), a strain gauge (3), a wave height meter (4), an anemometer (5), a rain gauge (6) and a current meter (7). After the scaled model (16) of the wind turbine is installed, the floating wind turbine real-time monitoring and intelligent control system simulates the on-site wind, rain and wave flow environment by adjusting the wave-making plate (11), the blower (12), the rainmaker (13), the water suction pump (14) and the water extraction pump (15). All measured data are summarized to the calculator (17) through the data integrator (19), and the parameters are corrected by the intelligent system to keep it similar to the on-site environment, thereby realizing the dual reproduction of the digital and physical models of the actual operating state of the on-site floating wind turbine.

2. The real-time monitoring and intelligent control system for floating wind turbines based on digital twins and environmental testing according to claim 1 is characterized in that: The field detection system comprises a wind turbine status detection module that uses a six-component meter to obtain wind turbine displacement and rotation data, a tension sensor to obtain mooring force data, and a strain gauge to obtain strain at a local position; a sea condition environment detection module that uses a wave height meter to obtain wave parameters, an anemometer to obtain wind speed and direction, a rain gauge to obtain rainfall, and a current meter to obtain flow velocity and direction; thereby transmitting the wind turbine operating status and environmental data to the digital twin system via a wireless signal station (8).

3. A real-time monitoring and intelligent control system for floating wind turbines based on digital twins and environmental testing according to claim 1 or 2, characterized in that: The on-site detection system is powered by the wind turbine itself and is equipped with solar cells as a backup power source.

4. The real-time monitoring and intelligent control system for floating wind turbines based on digital twins and environmental testing according to claim 1 is characterized in that: The digital twin system, in which the real-time monitoring module constructs a three-dimensional structure and environmental digital model of the on-site floating wind turbine, facilitates intuitive understanding of the on-site wind turbine status and surrounding environment; the environmental prediction module uses machine learning technology to predict the wind, wave, and current sea conditions in the future based on on-site wind and wave data, and uses this information as input conditions for model testing; the intelligent testing module is controlled by an intelligent system, and the system continuously learns and adjusts the liquid level in the liquid damper (9) and the length of the cable tractor (10) through test data to obtain the optimal solution for wind turbine vibration reduction control; the feedback control module feeds back the parameters of the liquid damper (9) and the cable tractor (10) to the site through a wireless signal station (8) to achieve the optimal control solution.

5. The real-time monitoring and intelligent control system for floating wind turbines based on digital twins and environmental testing according to claim 1 or 4, characterized in that: The wind, rain and wave flow parameters generated by the intelligent test module of the digital twin system are fed back to the calculator (17) in real time through the wave height meter (4), the anemometer (5), the rain gauge (6) and the current meter (7), and the wave parameters are controlled by adjusting the movement of the wave-making plate (11). The relationship between them is: Where H is the wave height, S is the wave-making plate stroke, k is the wave-making plate and wave frequency, and h is the water depth; the wind force is controlled by adjusting the speed of the blower (12); the rainfall is adjusted by adjusting the water pressure of the rainmaker (13); the flow rate and flow direction are adjusted by adjusting the power and distribution position of the water suction pump (14) and the water extraction pump (15). A wave-breaking area (21) is provided downstream of the pool to reduce the influence of backflow and improve the test accuracy.

6. The real-time monitoring and intelligent control system for floating wind turbines based on digital twins and environmental testing according to claim 1 is characterized in that: The liquid damper (9) is equipped with a wave height meter (4) and a bidirectional water pump (18) to adjust the liquid level of the liquid damper (9) so that the natural frequency of the liquid damper (9) is consistent with the shaking frequency of the floating fan to achieve the best damping effect; the natural frequency ω0 of the liquid damper is expressed as: Where A v and A h are the cross-sectional areas of the vertical and horizontal pipes of the U-shaped pipe, L v and L h are the lengths of the vertical and horizontal liquid columns in the TLMCD at the initial moment, respectively, and g is the acceleration due to gravity.

7. The real-time monitoring and intelligent control system for floating wind turbines based on digital twins and environmental testing according to claim 1 is characterized in that: The cable tractor (10) adjusts the cable length under the control of the intelligent system, continuously self-trains to obtain the optimal cable length under the current sea conditions, and provides the floating wind turbine with a restoring torque to ensure the stability of the wind turbine platform.

8. The real-time monitoring and intelligent control system for floating wind turbines based on digital twins and environmental testing according to claim 1 is characterized in that: The environmental simulation test system has a wave-making plate (11) that adjusts the wave direction and wind direction angle through a rotating device (22), a blower (12) that controls the wind direction angle and height through a crane, and adjusts the flow direction by starting a water suction pump (14) and a water extraction pump (15) at different positions.

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