LiDAR Wind Field Reconstruction for Turbine Control
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Solution Overview
Problem
Current LiDAR sensors in wind turbines face limitations in accuracy and data availability for estimating wind speed and direction, particularly in complex wind fields, leading to unreliable control strategies and increased maintenance costs due to misalignment and fatigue issues.
Innovation Solution
A method for acquiring and modeling a three-dimensional wind field using a LiDAR sensor by discretizing space into a grid of measurement and estimation points, applying a weighted recursive least squares optimization method to estimate wind amplitude and direction, and reconstructing the wind field in real-time, enabling precise wind speed and direction estimation upstream of the sensor.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If LiDAR sensors are used to measure wind speed, then remote sensing capability is improved, but measurement accuracy deteriorates due to indirect measurement and limited bandwidth
Solution Approach 1:
The patent segments the wind field measurement into multiple measurement axes (at least three distinct directions) rather than relying on a single LiDAR beam. This segmentation allows reconstruction of the full wind vector components (u, v, w) by combining measurements from multiple directions, thereby improving measurement accuracy while maintaining remote sensing capability
Solution Approach 2:
The patent introduces an intermediary reconstruction algorithm that processes the indirect LiDAR measurements and transforms them into accurate wind vector estimates. This intermediary computational step bridges the gap between the raw indirect measurements and the desired accurate wind field information
2Device complexity
If homogeneous wind field assumption is used for reconstruction, then algorithm simplicity is improved, but reconstruction accuracy deteriorates due to unrealistic wind field representation
Solution Approach 1:
The patent transitions from a static homogeneous wind field assumption to a dynamic wind field model that accounts for temporal variations and complex wind dynamics. The reconstruction algorithm adapts to changing wind conditions by using a dynamic model that reflects the actual turbulent and time-varying nature of atmospheric wind fields
Solution Approach 2:
The patent changes the fundamental parameters of the wind field model from constant homogeneous values to time-varying parameters that capture wind turbulence, shear, and other dynamic characteristics. This allows the reconstruction to accurately represent real wind field behavior while maintaining computational tractability
3Speed
If instantaneous wind speed estimation is implemented, then real-time control capability is improved, but longitudinal wind speed accuracy deteriorates due to moving average dependency
Solution Approach 1:
The patent performs preliminary reconstruction of the complete three-dimensional wind field (including longitudinal, lateral, and vertical components) before control applications are needed. This preliminary action provides accurate longitudinal wind speed estimates without relying on moving averages, enabling both real-time responsiveness and high accuracy simultaneously
4Measurement precision
If multiple measurement axes are used for wind vector reconstruction, then wind field estimation accuracy is improved, but data processing complexity increases
Solution Approach 1:
The patent merges the data from multiple measurement axes into a unified wind vector reconstruction framework. By combining the measurements systematically through a coordinated algorithm that processes all axes simultaneously rather than separately, the patent achieves accurate three-component wind vector estimation while managing computational complexity through integrated processing
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach provides reliable, real-time three-dimensional wind field reconstruction, enhancing wind turbine control, reducing maintenance costs, and improving operational efficiency by accurately predicting gusts and turbulence.
Implementation Method 1
LiDAR (Light Detection and Ranging) sensors used as a remote sensing method for measuring wind speed
Implementation Method 2
projection of the wind onto a measurement axis (also known as a laser beam for light amplification by stimulated emission of radiation)
Data Source
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AI summary
The subject matter of the invention relates to a method for acquiring and modelling an incident wind field by means of a LiDAR sensor. The acquisition and modelling includes a step for assessing the amplitudes and directions of the wind for a set of discrete points, as well as a step for reconstructing the incident wind field in three dimensions and in real time. The invention also relates to a method for controlling and/or monitoring a wind turbine provided with such a LiDAR sensor from the incident wind field reconstructed in three dimensions and in real time.