Abstract
Lidar based wind measurement is an integral part of wind farm control. The major issues and challenges in power maximization include the potential losses due to wake effect observed among wind turbines. This manuscript presents a wake management technique that utilizes lidar simulations for wake redirection.
The proposed methodology is validated for 2-turbine and 15-turbine wind farm layouts involving a PI control based yaw angle correction. Yaw angle misalignment using wake center tracking of the upstream turbines is used to increase the power generation levels. Results of wake center estimation are compared with a Kalman filter based method. Further, the velocity deficit and overall farm power improvement by yaw angle correction is calculated. Results reveal a 1.7% and 0.675% increase in total wind farm power for two different wind speed cases.
The proposed methodology is validated for 2-turbine and 15-turbine wind farm layouts involving a PI control based yaw angle correction. Yaw angle misalignment using wake center tracking of the upstream turbines is used to increase the power generation levels. Results of wake center estimation are compared with a Kalman filter based method. Further, the velocity deficit and overall farm power improvement by yaw angle correction is calculated. Results reveal a 1.7% and 0.675% increase in total wind farm power for two different wind speed cases.
Original language | English |
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Pages (from-to) | 484-493 |
Journal | Renewable Energy |
Volume | 152 |
Early online date | 13 Jan 2020 |
DOIs | |
Publication status | Published - 01 Jun 2020 |
Keywords
- Center of Wake
- Lidar
- Transfer function
- Velocity deficit
- Wake effect
- Yaw angle
ASJC Scopus subject areas
- Renewable Energy, Sustainability and the Environment