LiDAR Wind Speed Estimation Using Adaptive Kalman Filtering
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Solution Overview
Problem
Current wind turbine control and monitoring techniques fail to accurately determine average wind speed in the rotor plane using LiDAR sensors, as they require known distances from measurement planes to the rotor plane, limiting their configurability and precision.
Innovation Solution
A method employing a LiDAR sensor to measure wind speed in a vertical plane without a priori constraints on measurement plane distances, utilizing an adaptive Kalman filter to construct a wind model accounting for spatial and temporal coherence, allowing precise determination of average wind speed independent of measurement plane distances.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If LiDAR sensor is used to measure wind speed in the rotor plane, then wind speed measurement capability is improved, but the requirement for known distances from measurement planes to the rotor plane limits configurability and precision
Solution Approach 1:
The patent changes the measurement parameters by measuring wind speed at multiple altitudes (different z-coordinates) rather than requiring direct rotor plane measurement. By measuring at multiple parameter points (altitudes) and using interpolation, the system achieves precise rotor plane wind speed determination without requiring the LiDAR to be positioned at specific distances from the rotor plane.
Solution Approach 2:
The patent introduces an intermediary approach by measuring wind speed at multiple altitudes between the ground and the rotor plane, then using these intermediate measurements to infer the rotor plane wind speed. This intermediary measurement strategy eliminates the need for direct rotor plane measurement while maintaining precision.
2Measurement precision
If LiDAR sensor is positioned on the ground vertically oriented to measure wind field, then wind speed and direction measurement is improved, but the sensor cannot be used for real-time turbine control
Solution Approach 1:
The patent performs preliminary measurements at multiple altitudes to establish the vertical wind profile before the wind reaches the rotor plane. By having this preliminary data, the system can predict and prepare for upcoming wind conditions, enabling proactive control adjustments rather than reactive responses.
Solution Approach 2:
The system performs periodic measurements at multiple altitudes to continuously update the vertical wind profile. This periodic multi-altitude measurement approach provides continuous information about wind evolution, enabling timely control responses while maintaining measurement precision.
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
Enables precise and flexible determination of average wind speed in the vertical plane, enabling effective wind turbine control and optimization of power production without requiring specific LiDAR sensor configurations.
Implementation Method 1
a LiDAR (Light Detection And Ranging) sensor. LiDAR is a remote sensing or optical measurement technology based on the analysis of the properties of a beam returned to the emitter
Implementation Method 2
This sensor enables remote wind measurements
Implementation Method 3
using an adaptive Kalman filter to determine the wind speed
Data Source
AI summary
The present invention is a method of determining the average wind speed in a vertical plane by use of a LiDAR sensor (2), comprising performing measurements (MES), constructing a measurement model (MOD M) and a wind model (MOD V). Then an adaptive Kalman filter (KAL) is used to determine the wind speed (v), and determining the average wind speed in the vertical plane under consideration (RAWS).