A method and system for correcting the posture of a floating wind power station based on Beidou navigation

Abstract

The present application belongs to the technical field of floating wind power station maintenance, and particularly relates to a floating wind power station attitude correction method and system based on Beidou navigation. The method obtains the current position through the Beidou navigation system to generate correction parameters, and performs angle correction according to the correction parameters. Timing offset data is obtained to generate comparison parameters and trend parameters, and the comparison parameters and trend parameters are input into a function model to generate stable correction parameters. According to the correction trend estimated from the stable correction parameters and the periodic parameters, closed-loop control is performed to suspend or terminate the angle correction. The present application uses the Beidou navigation system to ensure the accuracy of the current position data, avoids over-correction and energy loss through multi-level closed-loop control logic, and comprehensively analyzes the timing offset data through the function model to achieve intelligent and high-robustness control of the floating attitude.

Description

Technical Field

[0001] This invention belongs to the field of floating wind power station maintenance technology, specifically relating to a floating wind power station attitude correction method and system based on Beidou navigation. Background Technology

[0002] As the global energy structure shifts towards cleaner and lower-carbon energy, wind power, as one of the most promising renewable energy sources, is expanding its technology and application scale at an unprecedented rate. In particular, in the field of offshore wind energy development, floating wind power technology is regarded as a key technological path for large-scale development of offshore energy in the future due to its unique advantages of being able to overcome water depth limitations and capture higher-quality wind resources in deep sea areas.

[0003] Existing floating wind power platforms exhibit weak attitude stability and position holding capabilities in complex marine dynamic environments, primarily due to the following two aspects: First, the attitude monitoring and control systems of existing platforms generally suffer from response lag. Traditional control architectures often rely on transmitting sensor data over long distances to a central processing unit for calculation, and then transmitting control commands back to the actuators. Under the rapidly changing coupling effects of waves, currents, and winds, this communication delay causes control decisions to lag significantly behind the actual attitude changes of the platform, making it difficult to achieve accurate and real-time dynamic compensation. Second, existing control strategies are relatively simple in function and have poor adaptability. Most systems adopt feedback control logic based on preset thresholds or fixed parameters, which cannot effectively identify and predict complex motion trends caused by nonlinear marine dynamics. Summary of the Invention

[0004] To address the aforementioned issues, this invention provides a method and system for attitude correction of floating wind power stations based on BeiDou navigation. By real-time monitoring of the floating device of the floating wind power station and generating correction parameters based on its drift direction, the system maintains the balance of the floating wind power station. Furthermore, during the correction process, the frequency of correction operations can be appropriately reduced, thereby reducing energy consumption while maintaining a relatively stable power generation state.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0006] Beneficial effects

[0007] The attitude correction method provided by this invention first obtains the current position of the floating wind power station through the BeiDou Navigation Satellite System, and calculates correction parameters including offset angle, drift direction and offset amount based on the position information and the preset reference angle. Therefore, this invention can ensure that the initial data source for attitude correction is accurate and reliable. By utilizing the high-precision, real-time three-dimensional spatial coordinates provided by the BeiDou Navigation Satellite System, the accuracy of the correction parameter calculation is guaranteed from the source, providing a solid data foundation for the subsequent angle correction process. This significantly improves the accuracy and final effect of the entire attitude correction process, ensuring that the floating wind power station can stably maintain the optimal power generation attitude.

[0008] This invention further constructs a multi-level closed-loop control logic. Specifically, the method estimates the correction trend by analyzing time-series offset data and decides to pause or continue angle correction based on the correction trend. At the same time, it determines the timing of terminating angle correction by comparing periodic parameters with preset thresholds and limits the correction frequency based on historical offset patterns. Through the above closed-loop control and pre-judgment logic, overcorrection or frequent fine-tuning caused by dynamic changes in sea state is effectively avoided. This logic can intelligently identify the state where attitude deviation has been suppressed or tends to be stable and pause or terminate angle correction in a timely manner, reducing the energy consumption and mechanical wear of the correction device and enhancing the overall stability of the floating wind power station's attitude.

[0009] When generating stable correction parameters, this invention inputs the comparison parameters selected from the time-series offset angle data, the calculated trend parameters, and the time-series offset data into a preset function model (such as an empirical parameter curve) for processing. This makes the correction strategy of this invention more adaptable and intelligent. In particular, when using an empirical parameter curve that matches the actual changing trend, it can accurately respond to nonlinear drift under complex sea conditions, further improving the precision and robustness of attitude control. Attached Figure Description

[0010] Figure 1 This is a flowchart of a method according to Embodiment 1 of the present invention. Detailed Implementation

[0011] Example 1

[0012] This embodiment provides a method for attitude correction of a floating wind power station based on BeiDou navigation. By combining the BeiDou navigation system with a dynamic attitude correction strategy, this method can accurately identify and correct the attitude of the floating wind power station during its operation on the sea surface in real time, thereby ensuring the long-term stability and safety of the equipment. The specific steps include the following:

[0013] The floating parameters of the floating wind power station are collected in real time. These parameters may include dynamic monitoring data on wind speed, wind direction, wave height, equipment rotation angle, and stress conditions. The current position of the floating wind power station is obtained through the Beidou navigation system. The current position is a three-dimensional spatial coordinate. For example, the navigation beacon positioning of a floating wind power station deployed in a certain area of ​​the sea can be updated in real time to (x1, y1, z1) coordinate data. At the same time, a preset reference angle is obtained. The reference angle is a reference attitude defined based on three-dimensional spatial coordinates. It not only includes a single azimuth angle, but also comprehensively defines the roll, pitch, and yaw angles of the platform under ideal working conditions, forming a complete three-dimensional attitude reference.

[0014] Based on the current position and a preset reference angle, the offset angle of the floating wind power station is calculated by comparing the current attitude reflected by the real-time acquired three-dimensional spatial coordinates with the reference attitude to obtain specific angular deviation values ​​in multiple dimensions such as roll, pitch, and yaw. These deviation values ​​together constitute the offset angle. Based on the offset angle, the drift direction of the floating wind power station is determined. Based on the offset angle, the corresponding offset amount is obtained. This offset amount is a quantified value of the physical adjustment required to offset the current offset angle, such as the amount of ballast water that needs to be moved, the magnitude of the torque that the adjustment unit needs to generate, etc. Combining the offset angle, drift direction, and offset amount, correction parameters are generated for subsequent correction operations.

[0015] Before proceeding to the actual attitude correction execution step, to avoid unnecessary energy consumption and mechanical wear caused by responding to too frequent transient disturbances, a pre-judgment step is added. This step compares the currently calculated offset with a preset historical offset pattern. This historical offset pattern is the result of statistical analysis of long-term operating data of floating wind power stations, which includes typical high-frequency, transient oscillation patterns with self-recovery characteristics under different sea conditions. By comparing the patterns, it can be identified whether the current offset belongs to this type of transient disturbance, and the correction frequency is determined accordingly. A frequency threshold is set. If the correction frequency exceeds the frequency threshold, it means that the platform is experiencing a brief fluctuation that may subside on its own. In this case, the system will not perform angle correction to improve the effectiveness and economy of the correction.

[0016] After confirming the need for correction, angle correction is performed on the floating wind turbine based on the drift direction included in the correction parameters. This process first determines the sign of the offset angle. If the offset angle is positive, a pure clockwise correction torque is applied by coordinating the symmetrically arranged adjustment units to adjust the platform attitude. Simultaneously, to avoid unnecessary translation or overturning effects, a clockwise symmetrical approach is used to adjust the floating wind turbine's attitude. If the offset angle is negative, a pure counterclockwise correction torque is applied by coordinating the symmetrically arranged adjustment units to adjust the platform attitude. Again, to avoid unnecessary translation or overturning effects, a counterclockwise symmetrical approach is used to adjust the floating wind turbine's attitude. Here, symmetry... The correction is not a simple unidirectional rotation, but is achieved through a correction device. The correction device includes multiple adjustment mechanisms arranged symmetrically around the platform's center of gravity. The purpose of this symmetrical layout is to minimize the generation of additional translational forces or overturning moments when applying correction torque, ensuring the purity of the correction action. The adjustment mechanism includes adjustment units and fixed units. The fixed unit is a base or shell rigidly connected to the main structure of the platform, while the adjustment unit is a component that can actively change the system's balance state, such as a water pump, a ballast moving slider, or a vector thruster. When performing clockwise symmetrical adjustment, it coordinates the drive of one or more pairs of adjustment units in symmetrical positions to generate a smooth clockwise correction torque, and vice versa.

[0017] While performing the correction, the system acquires and arranges a series of offset angle measurements in chronological order within a preset time period, setting them as time-series offset angle data. To identify persistent drift trends that require close attention, rather than temporary fluctuations, the system filters out continuous angle data segments from the time-series offset angle data that meet preset stability conditions. The preset stability conditions can be defined as the angle change rate being less than a preset change rate threshold within a certain time window, or the angle value fluctuating within a certain preset fluctuation range. Continuous angle data segments that meet these conditions are defined as comparison parameters because they represent the main and stable offset characteristics of the platform at the current stage. At the same time, the system acquires time-series offset data corresponding to the preset time period and calculates trend parameters based on the time-series offset data using linear regression or moving average methods. These trend parameters characterize the overall rate and direction of change of the offset during this period.

[0018] To achieve more refined control, the comparison parameters, trend parameters, and time-series offset data are input into a preset function model to generate stable correction parameters. The function model consists of preset empirical parameter curves, which are derived by analyzing and fitting a large amount of historical operating data. Each curve corresponds to a typical stable drift pattern and its optimal correction response strategy. The specific steps for generating stable correction parameters are as follows: First, determine if there is an empirical parameter curve among the preset empirical parameter curves that matches the changing trend of the comparison parameter. If so, the matching empirical parameter curve is used for calculation. This method can utilize historical experience to quickly generate the optimal stable correction parameters for the current specific operating condition. If not, it indicates that the system has encountered a new or atypical drift situation. In this case, a preset conventional algorithm, namely the PID control algorithm, is used to calculate and generate stable correction parameters, ensuring the robustness and adaptability of the system. The function model refers to a calculation model used to calculate the optimal stable correction parameters based on the platform's stable drift characteristics. Its specific formula is as follows:

[0019]

[0020] In the formula, The stability correction parameter represents the optimized correction control quantity that needs to be applied to counteract the stability offset, such as the target correction torque or the target displacement of the control unit. The stable offset angle is the average or characteristic angle deviation extracted from the parameters to be compared, representing the current stable offset state. The trend parameter represents the rate of change of the stable offset angle and is used to predict the future trend of the offset. This represents the instantaneous offset, which means the offset at a given time point. The offset, which is within the time window Integrals within This represents the cumulative offset effect during that period; These represent the dynamic gain coefficients, meaning that these coefficients represent the current steady state. The function, whose specific values ​​are determined by empirical parameter curves, represents the dynamic weights of proportional, derivative, and integral control terms, respectively, and is used to achieve the optimal control response for different drift modes. The empirical parameter curves refer to a set of pre-defined functions or lookup tables obtained through analysis and fitting of a large amount of historical data. These curves establish a stable drift state (characterized by the parameters to be compared and trend parameters) and the optimal control strategy (characterized by the dynamic gain coefficients in the function model). The mapping relationship between (reflected).

[0021] Based on the stable correction parameters, the correction trend is estimated. The correction trend is a numerical value used to characterize the degree of offset correction. It combines the residual amount and rate of change of the current offset. It is determined whether the correction trend is positive. A positive correction trend indicates that the offset has not been completely corrected, that is, the current correction force has not completely offset or exceeded the interference force of the external environment, and the offset may continue to develop. Conversely, a negative correction trend indicates that the offset has been suppressed, which means that the correction effect is significant, and the platform's attitude has become stable or is converging towards the reference attitude. If the correction trend is positive, the system continues to perform angle correction; if the correction trend is negative, the angle correction is paused and an observation period is entered to avoid overcorrection and save energy. In order to achieve dynamic fine-tuning of the correction force, the stable correction parameters are calculated by ratio with the preset single correction amount to generate correction parameters. The single correction amount represents the maximum or optimal adjustment range that the actuator can apply in a single action. This correction parameter can be used to guide the intensity of the next correction action to determine whether to perform a full-stroke adjustment or several small-step fine adjustments.

[0022] During the calibration process, the system continuously collects offset data and calculates the average of two consecutive offset data collections to obtain a periodic parameter. This periodic parameter reflects the fluctuation range of the platform's attitude under continuous calibration. The system determines whether the periodic parameter is less than a preset offset threshold, which is the upper limit of attitude tolerance set according to the safe operation standards of wind turbine generators. If the periodic parameter is less than the offset threshold, it indicates that the platform's attitude is stable within an acceptable range, so angle calibration continues to maintain this stable state. If the periodic parameter is not less than the offset threshold, it indicates that despite continuous calibration, the platform's offset fluctuation still exceeds the safe range. This may mean a sharp deterioration in sea conditions or equipment failure. In this case, angle calibration will be terminated, and an alarm may be triggered or the system may enter a safe shutdown mode to ensure the overall safety of the equipment.

[0023] In summary, this method utilizes the high-precision positioning characteristics and multi-parameter analysis capabilities of the BeiDou Navigation Satellite System to achieve comprehensive monitoring and correction of the operating status of floating wind power stations, effectively improving the adaptability and operating efficiency of marine wind power equipment in complex environments.

[0024] Example 2

[0025] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments. It should be understood that the specific embodiments described herein are merely for explaining the invention and are not intended to limit the scope of protection of the invention. This embodiment provides a floating wind power station attitude correction system based on BeiDou navigation, used to execute the above-described floating wind power station attitude correction method based on BeiDou navigation. It can monitor the attitude changes of the floating wind power station in real time, intelligently generate and execute correction strategies, and dynamically control the attitude correction process through a closed-loop evaluation mechanism, thereby ensuring the stability of the power station's attitude and operational safety. In specific implementation, it can be a dedicated control unit integrated into the main control system of the floating wind power station, or an independent hardware device, which internally includes a processor, memory, and an interface for communication with the BeiDou receiver and correction device. Logically, it can be divided into the following collaborative modules:

[0026] The position monitoring module, connected to the BeiDou Navigation Satellite System receiver installed on the floating wind power station, continuously acquires information representing the current position of the power station. Its core task is to monitor attitude deviation events. In a specific execution process, the real-time acquired current position is compared with a preset reference angle stored in the system. The reference angle represents the ideal, deviation-free reference attitude of the power station. Through this comparison, the module calculates an offset angle. The magnitude and sign of this offset angle represent the degree and direction of the current attitude deviation. When the calculated offset angle is determined to be non-zero, an attitude deviation event is identified, and the event and related offset angle data are transmitted to the correction decision module for further processing.

[0027] The correction decision module generates correction parameters to correct attitude deviations when responding to attitude deviation events detected by the position monitoring module. Based on the received offset angle, it determines the drift direction (e.g., clockwise or counterclockwise represented by a plus or minus sign), and retrieves the corresponding offset amount based on the offset angle. The offset angle, drift direction, and offset amount are combined to generate initial correction parameters. After generating the correction parameters, a pre-judgment is performed: the currently calculated offset is compared with preset historical offset patterns stored in the system. These historical patterns may include typical wave patterns under specific sea conditions. Through comparison, a correction frequency is determined. If this correction frequency exceeds a preset frequency threshold, it indicates that the current attitude deviation may be high-frequency and self-recovering. During normal oscillations, to avoid overcorrection leading to system instability, it will be decided not to perform this angle correction. It is responsible for generating decision-making basis for the correction evaluation module. It acquires and processes time series offset angle data and time series offset amount data within a preset time period. Specifically, it identifies parameters that meet preset stability conditions (e.g., fluctuation amplitude is less than a certain value) from the time series offset angle data as comparison parameters. It calculates a trend parameter based on the time series offset amount data. It inputs the comparison parameter, trend parameter, and original time series offset amount data into a preset function model to generate stable correction parameters and provides them to the correction evaluation module.

[0028] The attitude execution module acts as a bridge between decision-making and physical execution. Based on the correction parameters generated by the correction decision module, it performs angle correction on the floating wind power station. This module is connected to the correction device of the floating wind power station (e.g., mooring cable winch, thruster, or ballast water pump system). After receiving valid correction parameters, it determines the sign of the offset angle. If the offset angle is positive, it controls the correction device to adjust the attitude of the floating wind power station in a clockwise symmetrical manner. If the offset angle is negative, it controls the correction device to adjust the attitude of the floating wind power station in a counterclockwise symmetrical manner. The magnitude and force of the adjustment are determined based on the offset amount in the correction parameters until the attitude is restored to near the reference angle.

[0029] The calibration evaluation module evaluates the angle calibration process performed by the attitude execution module and generates periodic control commands to pause or terminate the angle calibration, thereby achieving closed-loop monitoring of the attitude calibration process. It executes two evaluation control logics: First, trend-based pause control receives stable calibration parameters generated by the calibration decision module and estimates a calibration trend based on these parameters. When the calibration trend is determined to be non-positive (i.e., the trend is stable or automatically converges towards the reference angle), it indicates that the external environmental force may be weakening or changing, and continuing active calibration may lead to overcalibration. A pause command is generated and sent to the attitude execution module to pause the current angle calibration. Second, real-time state-based termination control continuously acquires real-time offsets from the position monitoring module during the angle calibration execution and calculates a periodic parameter (e.g., the rate of change of offset or the cumulative value within a short time window) based on this data. When the periodic parameter is determined to be not less than a preset offset threshold, it indicates that the calibration action may have failed to produce the expected effect or even exacerbated attitude instability. To avoid further deterioration, a termination command is generated and sent to the attitude execution module to immediately terminate the current angle calibration.

[0030] Through the collaborative work of the aforementioned position monitoring module, correction decision module, attitude execution module, and correction evaluation module, the system in this embodiment can achieve precise, intelligent, and safe closed-loop control of the attitude of floating wind power stations. It can not only respond quickly based on real-time deviations, but also avoid unnecessary frequent corrections by combining historical deviation patterns. Furthermore, through dynamic evaluation and control of the attitude correction process, it effectively prevents the risks caused by over-correction or correction failure, thereby significantly improving the operational stability and power generation efficiency of floating wind power stations in complex marine environments. It is particularly suitable for unmanned offshore wind farms.

[0031] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for attitude correction of a floating wind power station based on BeiDou navigation, characterized in that, When it is determined that the current position of the floating wind power station has deviated from its attitude, the process includes: generating correction parameters based on the attitude deviation and performing angle correction according to the correction parameters; evaluating the execution process of angle correction and controlling the execution cycle of angle correction based on the evaluation results. Controlling the execution cycle of angle correction includes: generating stable correction parameters; estimating the correction trend based on the stable correction parameters; and pausing angle correction when the correction trend is non-positive. The process of generating stable correction parameters includes: acquiring time-series offset angle data and time-series offset amount data within a preset time period; identifying the comparison parameters that meet the preset stability conditions from the time-series offset angle data; calculating trend parameters based on the time-series offset amount data; and inputting the comparison parameters, trend parameters, and time-series offset amount data into a preset function model to generate stable correction parameters.

2. The attitude correction method for a floating wind power station based on BeiDou navigation according to claim 1, characterized in that, Controlling the execution cycle of angle correction also includes: During the correction process, offsets are continuously collected to calculate periodic parameters; Angle correction terminates when the periodic parameter is not less than the preset offset threshold.

3. The attitude correction method for a floating wind power station based on BeiDou navigation according to claim 1, characterized in that, Determining that the current position has deviated from its attitude includes: Obtain current location through the BeiDou Navigation Satellite System; Based on the current position and the preset reference angle, the offset angle is calculated to characterize the attitude deviation.

4. The attitude correction method for a floating wind power station based on BeiDou navigation according to claim 1, characterized in that, The generated correction parameters include: Determine the drift direction based on the offset angle; Determine the corresponding offset amount based on the offset angle; Combine offset angle, drift direction, and offset amount to generate correction parameters.

5. The attitude correction method for a floating wind power station based on BeiDou navigation according to claim 1, characterized in that, Before performing angle correction, the following is also included: The offset is compared with the preset historical offset pattern to determine the correction frequency; Angle correction is not performed when the correction frequency exceeds the preset frequency threshold.

6. The attitude correction method for a floating wind power station based on BeiDou navigation according to claim 1, characterized in that, Performing angle correction includes: Determine the sign of the offset angle; If the offset angle is positive, the attitude of the floating wind power station is adjusted by clockwise symmetry. If the offset angle is negative, the attitude of the floating wind power station is adjusted by using a counter-clockwise symmetry method.

7. A floating wind power station attitude correction system based on BeiDou navigation, characterized in that, include: The location monitoring module is used to obtain the current location of the floating wind power station through the Beidou navigation system in order to monitor its attitude deviation events; The correction decision module is used to generate correction parameters for correcting attitude deviations in response to attitude deviation events detected by the position monitoring module. The attitude execution module is used to perform angle correction on the floating wind power station based on the correction parameters generated by the correction decision module. The calibration evaluation module is used to evaluate the execution process of angle correction performed by the attitude execution module and generate periodic control commands for pausing or terminating angle correction. The process of generating stable correction parameters includes: acquiring time-series offset angle data and time-series offset amount data within a preset time period; identifying the comparison parameter that meets the preset stability conditions from the time-series offset angle data; calculating the trend parameter based on the time-series offset amount data; and inputting the comparison parameter, trend parameter, and time-series offset amount data into a preset function model to generate stable correction parameters.

8. The attitude correction system for a floating wind power station based on BeiDou navigation as described in claim 7, characterized in that, The correction decision module is also used for: Acquire time-series offset angle data and time-series offset amount data; Based on the time-series offset angle data, time-series offset data, and a preset function model, stable correction parameters are generated for the correction evaluation module to use in generating periodic control commands.

9. The attitude correction system for a floating wind power station based on BeiDou navigation as described in claim 8, characterized in that, The calibration and evaluation module is specifically used for: The correction trend is estimated based on the stability correction parameters, and a pause command is generated when the correction trend is non-positive. Calculate the periodicity parameter and generate a termination command when the periodicity parameter is not less than a preset offset threshold; The system also includes a calibration device; The attitude execution module is connected to the correction device and is used to perform angle correction by controlling the correction device.

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