Dynamic wake tracking using a cost-effective LiDAR and Kalman filtering: Design, simulation and full-scale validation

Wai Hou Lio, Gunner Chr. Larsen and Gunhild R. Thorsen

Renewable Energy, 2021, vol. 172, issue C, 1073-1086

Abstract: Wind turbines in a wind farm typically operate in the wake of other turbines, inevitably leading to a power loss and enhanced structural degradation of turbines downstream. Knowledge of the wake characteristics such as position and magnitude is valuable for optimising wind farm operations. An expensive multi-beam scanning Light Detection And Ranging system (LiDAR) can easily track and characterise the wake; however, this task is non-trivial for a cost-effective LiDAR with solely a few fixed laser beams. Therefore, this paper presents a dynamic wake tracking algorithm well-suited for a cost-effective LiDAR. The proposed algorithm estimates the lateral and vertical wake-centre positions by exploiting the wake meandering dynamics and Kalman filtering. Numerical simulation results showed that the wake tracking performance by the proposed method was remarkably successful in the low turbulent wind field, and robust to any changes in the vertical mean wind shear. Similarly, in full-scale validation, the proposed algorithm using a fixed beam LiDAR demonstrated its reliable wake tracking capability that surprisingly was as good as traditional methods based on a multi-beam scanning LiDAR. Thus, the proposed algorithm presents a cost-effective alternative to track the wake movement, which is particularly valuable for numerous applications, for example, closed-loop wake steering control.

Keywords: Dynamic wake meandering; Kalman filtering; State estimation; Wake characterization; Wake detection; Wake steering control (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:172:y:2021:i:c:p:1073-1086

DOI: 10.1016/j.renene.2021.03.081

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