A multi-parameter adaptive control method for an electric heating region of a wind turbine blade
By employing a multi-parameter adaptive control method, combined with multi-source sensors and a simulation database, the icing area of wind turbine blades is dynamically predicted, achieving a highly efficient and low-energy-consumption de-icing effect. This solves the problem of energy consumption and efficiency imbalance in existing technologies and is suitable for de-icing wind turbine blades in complex environments.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- ZHUZHOU TIMES NEW MATERIAL TECHNOLOGY CO LTD
- Filing Date
- 2026-05-27
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies cannot effectively balance energy consumption and efficiency during wind turbine blade de-icing. Especially in complex and variable environments, conventional heating methods cannot accurately locate the icing area, resulting in increased energy consumption and poor de-icing effect.
A multi-parameter adaptive control method is adopted, which monitors blade motion, environmental parameters and unit status through multi-source sensors, and combines simulation database analysis to dynamically predict icing areas and perform zoned heating to achieve precise de-icing.
It achieves efficient and low-energy de-icing, adapts to complex environmental changes, improves the targeting and safety of de-icing, reduces power consumption, and has self-learning capabilities.
Smart Images
Figure CN122407486A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of wind turbine blade technology, and specifically provides a multi-parameter adaptive control method for the electrically heated region of a wind turbine blade. Background Technology
[0002] With the increasing prominence of environmental issues and energy crises, clean and renewable energy has received attention from all countries. Wind energy, as a renewable resource, has huge reserves and wide distribution, and has good development and utilization potential. Wind turbine generator sets are devices that convert wind energy into electrical energy. Through the aerodynamic performance of the wind turbine blades, the pressure difference generated when the wind passes over the blades drives the blades to rotate, which in turn drives the hub and main shaft to rotate. The main shaft inputs power into the gearbox, and after the gearbox changes speed, it transmits torque to the generator, which drives the generator rotor to rotate and generate electrical energy.
[0003] During actual operation, wind turbines face many problems, especially in southern regions where winter temperatures are low and the environment around the turbines is humid. Ice formation on the blade surface is very likely to occur. Ice formation on the blade surface can affect the overall power generation efficiency of the turbine, and in severe cases, it may lead to major operational accidents. Once ice forms on the blade surface, it is necessary to remove the ice as soon as possible.
[0004] Electric heating for wind turbine blade de-icing is currently the mainstream and reliable method for removing icing. This method employs a control logic that heats different areas of the blade in segments to effectively remove icing while reducing energy consumption. During wind turbine operation, wind speed, wind direction, icing on the blade surface, and turbine pitch control cause changes in the blade's predetermined angle of attack, leading to changes in the flow field near the blade. This, in turn, causes regional variations in icing on the blade surface. Conventional methods that rely solely on temperature for segmented heating may not be able to accurately locate severely iced areas in complex and variable environments, significantly reducing the effectiveness of segmented heating for de-icing and increasing energy consumption.
[0005] Among existing technologies, the following patents relate to wind turbine blade de-icing: 1. Patent document CN112096577A, entitled "A Wind Turbine Blade De-icing Device," mentions multi-sensor fusion but fails to achieve dynamic adaptive adjustment of heating power, thus failing to solve the balance between energy consumption and efficiency. 2. Patent document CN116857134A, entitled "A Segmented Electric Heating Device for Wind Turbine Blades," discloses a segmented electric heating device that controls segmented heating through electrode groups, but does not involve multi-parameter collaborative control and energy efficiency optimization, thus failing to achieve dynamic adjustment and resulting in high energy consumption. 3. Patent document CN118775185A, entitled "A Wind Turbine Blade Heating and De-icing Method and Device," proposes de-icing timing control based on a predictive model, but relies on a single LSTM model, which lacks adaptability to complex environments and fails to solve the balance between energy consumption and efficiency.
[0006] Therefore, there is an urgent need for a de-icing control system that can comprehensively sense the environment, icing status, and heating system parameters, and achieve closed-loop optimization. Summary of the Invention
[0007] To address the aforementioned problems, this invention provides a multi-parameter adaptive control method for the electric heating zone of wind turbine blades. Through deep collaboration of multi-source sensing, intelligent decision-making, and dynamic execution, it achieves high efficiency, low energy consumption, and intelligent blade de-icing.
[0008] This invention provides a multi-parameter adaptive control method for the electric heating zone of a wind turbine blade, comprising the following steps: S1: The wind turbine blade movement amplitude, blade temperature, ambient wind speed and humidity are monitored in real time through the heating and de-icing control system; S2: Using the icing range of wind turbine blades as a condition for predicting the icing area: When it is determined that icing has occurred on the surface of the wind turbine blades and the ambient wind speed is within a safe range, the offset is calculated based on the monitored blade movement amplitude, and the area where the wind turbine blades may ic up is analyzed based on the offset. The icing thickness of wind turbine blades is used as the second condition for predicting the icing area: when the icing thickness reaches or exceeds the first preset thickness threshold, the icing area is dynamically analyzed based on the simulation database. Using the pitch and yaw errors of the wind turbine as the third condition for predicting the icing area: When it is determined that there is an error in the pitch or yaw of the wind turbine, the pitch angle difference, yaw angle difference, and yaw rate are calculated based on the monitored wind speed and wind direction, and it is determined whether the error exceeds the limit; if it exceeds the limit, the pitch or yaw operation is repeated; if it does not exceed the limit, the icing area on the surface of the wind turbine blade is predicted in combination with the error situation. S3: Integrate the conditions for predicting the icing area (condition 1, condition 2, and condition 3) to determine the de-icing area that the wind turbine blades ultimately need to be heated for. S4: The heating and de-icing control system controls the independent heating zones corresponding to the target heating area on the surface of the wind turbine blades and performs de-icing.
[0009] Furthermore, the heating and de-icing control system includes a multi-source sensing module, an environmental monitoring module, a zoned heating module, and a control processing module; S1 collects blade motion amplitude data through a multi-source sensing module and monitors the surface temperature of the wind turbine blade, ambient wind speed and ambient humidity through an environmental monitoring module. In S4, zone heating is performed through a zone heating module, which includes multiple independent and controllable heating zones arranged on the blade surface. The control and processing module is electrically connected to the multi-source sensing module, the environmental monitoring module, and the zone heating module, respectively.
[0010] The multi-source sensing module includes fiber optic sensors installed inside the wind turbine blades. The fiber optic sensors are used to monitor the flapping and oscillation amplitudes of the wind turbine blades and transmit the motion amplitude data of the wind turbine blades to the control processing module for analysis and processing via transmission lines.
[0011] Furthermore, in S2, when the icing range of the wind turbine blades is used as a condition for predicting the icing area, it is determined whether the blades are icing when the ambient temperature is below 0°C, and at the same time, it is monitored whether the ambient wind speed is greater than the safe wind speed threshold. If the wind turbine blades ice up and the monitored ambient wind speed is greater than the safe wind speed threshold, the unit must be shut down, the zone heating module must be turned off, and an alarm must be issued to prevent the unit from malfunctioning. If wind turbine blades ice up and the monitored ambient wind speed is less than the safe wind speed threshold, the movement amplitude of the wind turbine blades is monitored by fiber optic sensors, and the movement offset of the wind turbine blades is calculated. Based on the offset, the area where the wind turbine blades may ice up is analyzed, and the predicted area is used as one of the conditions for starting heating and de-icing.
[0012] Furthermore, the safe wind speed threshold is 25 m / s.
[0013] Furthermore, when the icing thickness of wind turbine blades is used as the second condition for predicting the icing area, the icing range is determined by simulation in response to the impact of icing thickness. This icing thickness simulation analysis database is then used as the second condition for predicting the icing area.
[0014] Furthermore, when the ice thickness is greater than or equal to 3 mm, the simulation results are used to analyze the ice region database and dynamically analyze the zoned heating areas.
[0015] Furthermore, when using the pitch and yaw errors of the turbine as the third condition for predicting the icing area, after it is determined that there is an error in the pitch or yaw of the turbine, the pitch angle difference, yaw angle difference, and yaw rate are calculated based on the monitored wind speed and wind direction. At the same time, it is determined whether the error exceeds the limit. If it exceeds the limit, the pitch or yaw operation needs to be repeated. If it does not exceed the limit, the surface icing area of the wind turbine blade is predicted in combination with the error situation, and the icing range is used as the third condition for predicting the icing area when the heating area is turned on.
[0016] Furthermore, the pitch angle difference threshold is 1° and the yaw angle difference threshold is 8°. When the pitch angle difference threshold exceeds 1° or the yaw angle difference threshold exceeds 8°, the pitch or yaw operation needs to be performed again.
[0017] Furthermore, by analyzing the predicted icing range of the wind turbine blades based on the combined motion amplitude, icing thickness, and pitch and yaw errors, the de-icing area requiring final heating of the wind turbine blades is determined. When the de-icing thickness is less than 1 mm, the motion amplitude, pitch, and yaw errors of the wind turbine blades are re-analyzed, and the heating area is updated. Heating is stopped once there is no risk of icing, and the above data is saved to the database.
[0018] Compared with the prior art, the present invention can achieve the following beneficial effects: 1. Accurate prediction and efficient de-icing: By integrating real-time blade motion data, ice thickness development models, and unit control errors, the core ice-forming area is predicted dynamically and in multiple dimensions. This changes the limitations of traditional methods that rely solely on fixed-point temperatures or single environmental parameters, allowing the selection of heating areas to be highly matched with the actual high-risk ice-forming areas, greatly improving the targeting and effectiveness of de-icing.
[0019] 2. Energy saving and consumption reduction: Due to accurate prediction, "overheating" (i.e., heating areas without ice or with thin ice) and "underheating" (i.e., failing to heat areas with heavy ice) can be avoided to the greatest extent. Heating only areas that need de-icing significantly reduces the energy consumption of the electric heating system and improves the overall operating economy of the wind turbine.
[0020] 3. Strong adaptability and high safety: The system can respond to various dynamic changes such as blade flexible deformation, ice growth, and unit attitude adjustment, realizing true adaptive control. It is especially suitable for wind farm environments with complex and ever-changing operating conditions. It has built-in safe wind speed judgment logic to prioritize the safety of the unit under severe wind conditions, avoiding the risk that de-icing operations may aggravate the unit load.
[0021] 4. Intelligent and self-learning potential: Data generated during the control process (such as predicted area, actual de-icing effect, and environmental parameters) can be saved to the database, providing a data foundation for subsequent optimization of the prediction model and correction of the simulation database, enabling the system to have the potential for continuous improvement. Attached Figure Description
[0022] Figure 1 This is a flowchart illustrating the implementation of multi-parameter adaptive zoned heating and de-icing for wind turbine generators according to an embodiment of the present invention. Figure 2 This is a schematic diagram of the change in icing position of the airfoil at different angles of attack according to an embodiment of the present invention (where line L is the schematic line of the icing area). Figure 3 This is a schematic diagram of the arrangement of fiber optic sensors in a wind turbine blade according to an embodiment of the present invention; Figure 4 This is a schematic diagram of the heating zone of a wind turbine blade according to an embodiment of the present invention.
[0023] The attached reference numerals include: 1. Wind turbine blade; 2. Fiber optic sensor; 3. Transmission line; 4. Control and processing module; 5. Leading edge heating zone; 6. Optimized heating zone. Detailed Implementation
[0024] To make the objectives, technical solutions, and advantages of this invention clearer, the following description is provided in conjunction with the appendix. Figure 1-4 The present invention will be further described in detail below with reference to specific embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and do not constitute a limitation thereof.
[0025] A multi-parameter adaptive control method for the electric heating zone of a wind turbine blade includes the following steps: S1: The heating and de-icing control system monitors the movement amplitude, blade temperature, ambient wind speed, and humidity of the wind turbine blade 1 in real time. The heating and de-icing control system includes a multi-source sensing module, an environmental monitoring module, a zoned heating module, and a control processing module 4. The multi-source sensing module collects the movement amplitude data of the blade, and the environmental monitoring module monitors the surface temperature, ambient wind speed, and ambient humidity of the wind turbine blade 1. The control processing module 4 is electrically connected to the multi-source sensing module, the environmental monitoring module, and the zoned heating module.
[0026] The multi-source sensing module includes an optical fiber sensor 2 installed inside the wind turbine blade 1. The optical fiber sensor 2 is used to monitor the swing amplitude and oscillation amplitude of the wind turbine blade 1, and transmits the motion amplitude data of the wind turbine blade 1 to the control processing module 4 for analysis and processing via the transmission line 3.
[0027] S2: Using the icing range of wind turbine blade 1 as a condition for predicting the icing area: When it is determined that icing occurs on the surface of wind turbine blade 1 and the ambient wind speed is within a safe range, the offset is calculated based on the monitored blade movement amplitude, and the area where wind turbine blade 1 may ic up is analyzed based on the offset.
[0028] During wind turbine operation, parameters such as temperature, wind speed, and humidity of wind turbine blade 1 are monitored and collected in real time. When the monitored ambient temperature is below 0℃, it is determined whether the blade is icing. At the same time, it is monitored whether the ambient wind speed is greater than the safe wind speed threshold. If the wind turbine blade 1 is icing and the monitored ambient wind speed is greater than the safe wind speed threshold, the unit needs to be shut down, the zone heating module needs to be turned off, and an alarm needs to be issued to prevent the unit from malfunctioning.
[0029] If wind turbine blade 1 ices up and the monitored ambient wind speed is less than the safe wind speed threshold, the motion amplitude of wind turbine blade 1 is monitored by fiber optic sensor 2, such as the flapping amplitude (A_flap: 1.5-3°) and sway amplitude (A_edge: 0.5-2°), and the motion offset of wind turbine blade 1 is calculated. Based on the offset analysis, the area where the wind turbine blade 1 may ic up is analyzed, and the predicted area is used as one of the conditions for starting the heating and de-icing. In this embodiment, the safe wind speed threshold is 25 m / s.
[0030] When the surface icing of wind turbine blade 1 reaches a certain thickness, it will cause a change in the angle of attack of the airfoil surface, which in turn will lead to a change in the icing area. The icing thickness of wind turbine blade 1 is used as the second condition for predicting the icing area: when the icing thickness reaches or exceeds the first preset thickness threshold, the icing area is dynamically analyzed based on the simulation database. The icing range is determined by simulation in response to the impact of the icing thickness. When the icing thickness is greater than or equal to 3 mm, the icing area database is analyzed by calling the simulation results, and the heating area is dynamically analyzed. Thus, the icing thickness simulation analysis database is used as the second condition for predicting the icing area.
[0031] When the wind direction changes, the turbine will perform pitch and yaw operations. However, due to possible errors in the pitch system's judgment, the final pitch condition may have some error, resulting in the icing area of the wind turbine blade 1 being different from the initial heating area. The pitch and yaw error of the turbine is used as the third condition for predicting the icing area: When it is determined that there is an error in the pitch or yaw of the turbine, the pitch angle difference, yaw angle difference, and yaw rate are calculated based on the monitored wind speed and wind direction. It is then determined whether the error exceeds the limit. If it exceeds the limit, the pitch or yaw operation is repeated. If it does not exceed the limit, the icing area on the surface of the wind turbine blade 1 is predicted based on the error.
[0032] When using pitch and yaw errors as the third condition for predicting the icing area, after determining that there is an error in the pitch or yaw, the pitch angle difference, yaw angle difference, and yaw rate are calculated based on the monitored wind speed and direction. At the same time, it is determined whether the error exceeds the limit. If it exceeds the limit, the pitch or yaw operation needs to be repeated. If it does not exceed the limit, the icing area on the surface of the wind turbine blade 1 is predicted based on the error, and the icing range is used as the third condition for predicting the icing area when the heating area is turned on. In this embodiment, the pitch angle difference threshold is 1°, and the yaw angle difference threshold is 8°. When the pitch angle difference threshold exceeds 1° and the yaw angle difference threshold exceeds 8°, the pitch or yaw operation needs to be repeated.
[0033] S3: By integrating three conditions for predicting the icing area, the final de-icing area requiring heating for wind turbine blade 1 is determined. Specifically, the icing range predicted by the wind turbine blade 1's motion amplitude, the icing range predicted by the wind turbine blade 1's icing thickness, and the icing range predicted by the turbine's pitch and yaw errors are analyzed to determine the final de-icing area requiring heating for wind turbine blade 1. When the heating and de-icing thickness is less than 1 mm, the motion amplitude, pitch, and yaw errors of wind turbine blade 1 are re-analyzed, and the heating area is updated. Heating is stopped when there is no risk of icing, and the above data is saved to the database. This method enables effective de-icing, avoids situations where partial icing cannot be removed, and also avoids energy waste caused by opening most of the heating area.
[0034] S4: The heating and de-icing control system controls the independent heating zones corresponding to the target heating area on the blade surface and performs de-icing. In S4, the partitioned heating module performs partitioned heating. The partitioned heating module includes multiple independent and controllable heating zones arranged on the surface of the wind turbine blade 1. The surface heating zone of the wind turbine blade 1 is divided into the leading edge heating zone 5 and the optimized heating zone 6. Determining the heating zone and adjusting the zone is mainly for the optimized heating zone 6 of the wind turbine blade 1. Based on the above process, the icing area on the surface of the wind turbine blade 1 is determined, and the required heating area in the optimized heating zone 6 is activated accordingly to achieve precise, efficient and comprehensive de-icing.
[0035] Although embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention.
[0036] The specific embodiments of the present invention described above do not constitute a limitation on the scope of protection of the present invention. Any other corresponding changes and modifications made in accordance with the technical concept of the present invention should be included within the scope of protection of the claims of the present invention.
Claims
1. A multi-parameter adaptive control method for the electric heating zone of a wind turbine blade, characterized in that, Includes the following steps: S1: The movement amplitude, blade temperature, ambient wind speed and humidity of the wind turbine blades (1) are monitored in real time through the heating and de-icing control system; S2: The icing range of the wind turbine blade (1) is used as the condition for predicting the icing area: When it is determined that icing occurs on the surface of the wind turbine blade (1) and the ambient wind speed is within a safe range, the offset is calculated based on the monitored blade movement amplitude, and the area where the wind turbine blade (1) may ic up is analyzed based on the offset. The icing thickness of the wind turbine blade (1) is used as the second condition for predicting the icing area: when the icing thickness reaches or exceeds the first preset thickness threshold, the icing area is dynamically analyzed based on the simulation database. Using the pitch and yaw errors of the unit as the third condition for predicting the icing area: When it is determined that there is an error in the pitch or yaw of the unit, the pitch angle difference, yaw angle difference and yaw rate are calculated based on the monitored wind speed and wind direction, and it is determined whether the error exceeds the limit; if it exceeds the limit, the pitch or yaw operation is repeated; if it does not exceed the limit, the surface icing area of the wind turbine blade (1) is predicted in combination with the error situation. S3: Combine the conditions for predicting the icing area, the conditions for predicting the icing area, and the conditions for predicting the icing area to determine the de-icing area that the wind turbine blades (1) ultimately need to be heated. S4: Control the independent heating zones corresponding to the target heating area on the surface of the wind turbine blade (1) through the heating and de-icing control system, and perform de-icing.
2. The multi-parameter adaptive control method for the electric heating zone of wind turbine blades according to claim 1, characterized in that, The heating and de-icing control system includes a multi-source sensing module, an environmental monitoring module, a zoned heating module, and a control processing module (4); In S1, the motion amplitude data of the blade is collected by the multi-source sensing module, and the surface temperature, ambient wind speed and ambient humidity of the wind turbine blade (1) are monitored by the environmental monitoring module. In S4, zone heating is performed through a zone heating module, which includes multiple independent and controllable heating zones arranged on the blade surface. The control processing module (4) is electrically connected to the multi-source sensing module, the environmental monitoring module and the zone heating module respectively.
3. The multi-parameter adaptive control method for the electric heating zone of wind turbine blades according to claim 2, characterized in that, The multi-source sensing module includes an optical fiber sensor (2) installed inside the wind turbine blade (1). The optical fiber sensor (2) is used to monitor the swing amplitude and oscillation amplitude of the wind turbine blade (1) and transmits the motion amplitude data of the wind turbine blade (1) to the control processing module (4) for analysis and processing via the transmission line (3).
4. The multi-parameter adaptive control method for the electric heating zone of wind turbine blades according to claim 3, characterized in that, In S2, when the icing range of the wind turbine blade (1) is used as a condition for predicting the icing area, it is determined whether the blade is icing when the ambient temperature is below 0℃, and at the same time, it is monitored whether the ambient wind speed is greater than the safe wind speed threshold. If the wind turbine blades (1) freeze and the monitored ambient wind speed is greater than the safe wind speed threshold, the unit must be shut down, the zone heating module must be turned off, and an alarm must be issued to prevent the unit from malfunctioning. If the wind turbine blade (1) ices up and the monitored ambient wind speed is less than the safe wind speed threshold, the movement amplitude of the wind turbine blade (1) is monitored by the fiber optic sensor (2), and the movement offset of the wind turbine blade (1) is calculated. Based on the offset, the area where the wind turbine blade (1) may ic up is analyzed, and the predicted area is used as one of the conditions for starting the heating and de-icing.
5. The multi-parameter adaptive control method for the electric heating zone of wind turbine blades according to claim 4, characterized in that, The safe wind speed threshold is 25 m / s.
6. The multi-parameter adaptive control method for the electric heating zone of wind turbine blades according to claim 5, characterized in that, When the icing thickness of the wind turbine blade (1) is used as the second condition for predicting the icing area, the icing range is determined by simulation in response to the influence of the icing thickness. The icing thickness simulation analysis database is then used as the second condition for predicting the icing area.
7. The multi-parameter adaptive control method for the electric heating zone of wind turbine blades according to claim 6, characterized in that, When the ice thickness is greater than or equal to 3mm, the simulation results are used to analyze the ice region database and dynamically analyze the zoned heating area.
8. The multi-parameter adaptive control method for the electric heating zone of wind turbine blades according to claim 7, characterized in that, When the pitch and yaw errors of the unit are used as the third condition for predicting the icing area, after it is determined that there is an error in the pitch or yaw of the unit, the pitch angle difference, yaw angle difference and yaw rate are calculated based on the monitored wind speed and wind direction, and it is determined whether the error exceeds the limit. If it exceeds the limit, the pitch or yaw operation needs to be repeated. If it does not exceed the limit, the surface icing area of the wind turbine blade (1) is predicted in combination with the error situation, and the icing range is used as the third condition for predicting the icing area of the heating area.
9. The multi-parameter adaptive control method for the electric heating zone of wind turbine blades according to claim 8, characterized in that, The pitch angle difference threshold is 1°, and the yaw angle difference threshold is 8°. When the pitch angle difference threshold exceeds 1° or the yaw angle difference threshold exceeds 8°, the pitch or yaw operation must be repeated.
10. The multi-parameter adaptive control method for the electric heating zone of wind turbine blades according to claim 9, characterized in that, The icing range of the wind turbine blade (1) is predicted by the combined motion amplitude of the wind turbine blade (1), the icing range of the wind turbine blade (1) is predicted by the icing thickness of the wind turbine blade (1), and the icing range of the wind turbine blade (1) is predicted by the pitch and yaw errors of the turbine unit. The de-icing area that the wind turbine blade (1) needs to be heated is determined. When the heating and de-icing thickness is less than 1 mm, the motion amplitude, pitch and yaw errors of the wind turbine blade (1) are re-analyzed and the heating area is updated. Heating is stopped when there is no risk of icing and the above data is saved to the database.