J. Gutknecht
7 records found
1
Wake Recovery Enhancement with Helix Active Wake Control
Vortex Structures in a Porous Disk Wake Observed in PIV Experiments
Power losses at waked turbines due to the energy extraction of upstream turbines from the flow pose a major risk to the economic feasibility of wind farms. Helix active wake control has proven its potential to mitigate these wake-induced power losses by accelerating the recovery
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Synergizing Helix Active Wake Mixing with Dynamic Yawing
An Exploration Study using Porous Discs in a Wind Tunnel
Clustering multiple turbines in close vicinity gives rise to efficiency losses due to the energy extraction of upstream turbines, a phenomenon known as the wake effect. The risk wake-induced power losses pose for the economic feasibility of wind farm projects motivated several me
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Wake mixing techniques like the Helix have shown to be effective at reducing the wake interaction between turbines, which improves wind farm power production. When these techniques are applied to a floating turbine it will excite movement. The type and magnitude of movement are d
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In recent years, the relevance of the interaction between neighboring wind farms has grown steadily. As one farm extracts energy from the wind, a downstream one can systematically experience lower wind speeds which threatens the economic viability of the farm. Significant progres
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Dynamic individual pitch control for wake mitigation
Why does the helix handedness in the wake matter?
Wind farm flow control aims at mitigating wake effects in order to maximize power production in wind farms. This work mostly focuses on the Helix strategy, which relies on individual pitch control to radially offset the application point of the thrust force from the rotor center
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A promising method to reduce wake effects in offshore wind farms is the Helix approach, which increases the mixing of the wake with the surrounding flow by exciting the individual blade pitch. This increases the wind speed in the wake, resulting in a higher power output at a down
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Dynamic Mode Decomposition (DMD) is a fully data-driven method to extract a linear system from experimental or numerical data. It has proven its suitability for modeling wind turbine wakes, particularly those generated with Dynamic Induction Control (DIC), a method to reduce the
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