Wind Farm Wake Behavior Determination via Atmospheric Instability Metrics
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Solution Overview
Problem
Existing methods for determining wake behavior in wind farms and controlling wind turbines to mitigate wake effects are less robust due to changes in the surroundings, such as obstacles, which can lead to inaccurate free-stream wind turbulence measurements.
Innovation Solution
A method that determines a metric indicative of atmospheric instability for multiple wind turbines, selects a set of wind turbines with the lowest instability, and uses these conditions to determine wake behavior and control setpoints for wind turbines, thereby adapting to changes in the wind farm layout or geometry.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If free-stream wind turbulence measurements are used to determine wake behavior, then control accuracy is improved, but reliability deteriorates due to changes in surroundings such as obstacles
Solution Approach 1:
The patent segments the wind farm into multiple groups based on wake exposure levels (first group with higher wake exposure, second group with lower wake exposure). By dividing the wind farm and selecting reference wind turbines from the second group that are least affected by wakes, the system maintains reliable turbulence measurements even when surroundings change, thus resolving the contradiction between measurement precision and reliability
Solution Approach 2:
The patent introduces an intermediary selection process that identifies reference wind turbines from the second group as mediators between the raw turbulence measurements and the wake behavior determination. These selected reference turbines serve as reliable intermediaries whose measurements are used to determine atmospheric stability and wake behavior, overcoming the unreliability caused by environmental changes
2Device complexity
If only front wind turbines are used for deriving control setpoints, then device complexity is reduced, but adaptability deteriorates when wind farm layout changes
Solution Approach 1:
The patent implements a dynamic selection process where reference wind turbines are not fixed to only the front position but are dynamically selected from the second group based on current wake exposure conditions. This dynamic approach allows the control system to adapt to changing wind farm layouts and wake patterns while maintaining reasonable complexity, as the selection is based on operational data rather than fixed geometric positions
Solution Approach 2:
The patent makes the reference wind turbine selection universal by allowing any wind turbine from the second group to serve as a reference, not just front wind turbines. This multi-functionality enables the same control methodology to work across different wind farm configurations and layouts, improving adaptability while keeping the control system framework unchanged
Data Source
AI summary
The present disclosure relates to methods (100, 200) for determining wake behavior in a wind farm. A method (100) comprises determining (100) a metric that is indicative of atmospheric instability for a plurality of wind turbines in the wind farm, selecting (120) a set of wind turbines of the plurality of wind turbines for which the corresponding metric indicates lowest atmospheric instability, determining (130) the atmospheric instability based on wind conditions at the selected set of wind turbines, and determining (140) the wake behavior in the wind farm based on the determined atmospheric instability. The present disclosure further relates to wind farm controllers (36), wind turbines (10) and wind farms.