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Delegates are invited to meet and discuss with the poster presenters in this topic directly after the session 'Remote sensing: From toys to tools?' taking place on Wednesday, 12 March 2014 at 14:15-15:45. The meet-the-authors will take place in the poster area.

Ndaona Chokani ETH Zurich, Switzerland
Mohsen Zendehbad (1) F P Ndaona Chokani (1) Reza Abhari (1)
(1) ETH Zurich, Zurich, Switzerland

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Large area measurements of wind speed using a mobile-based lidar


Wakes are the source of 10-20% underperformance of wind farms [1]. Moreover, fatigue loads on turbines in wakes increase by up to 80% [2]. To reduce turbine lifecycle costs, computational tools for micrositing of wind turbines are being developed [3]. To-date, few suitable full-scale measurements [4-6] are available to support the development of these tools. A mobile-based LIDAR system, which has lower cost-of-ownership and is more easily and quickly deployed than prior systems, has been developed. This innovation makes advanced remote sensing technology more accessible and realisable for the wind industry – that is, a tool rather a toy.


The mobile-based LIDAR system, windRover II, is comprised of a 3D scanning LIDAR that is installed in a customised van. The van provides a two-person crew with working and living quarters. Independent power generation and telecommunications systems in windRover II make off-road deployment for extended periods of time possible. The LIDAR’s high spatial resolution of 12m, angular pointing accuracy of ±0.1°, and accuracy in wind speed measurements, ±0.08m/s, enable detailed flowfield measurements to be made in utility-scale wind farms. In-house developed software packages with auxiliary instrumentation are used to operate the LIDAR in the stationary or moving windRover II.

Main body of abstract

In the final paper, results from several recent measurement campaigns using this novel, innovative and practical engineering system shall be presented. Measurements at a 25.8MW wind farm in the flat terrain of northern Germany, simultaneously detail the wake-wake interactions between nine multi-megawatt wind turbines; this is accomplished by making measurements from the moving windRover II. It is shown that the streamwise extents of the wakes differ. These differences highlight the importance of site-specific, optimised micrositing of turbines. The measurements compare favourably with CFD simulations. In another campaign at Switzerland’s largest wind farm that is in complex terrain, all wind speed components in the near-, intermediate- and far-wakes of multiple wind turbines are detailed. This is accomplished by making measurements from three different stationary positions of windRover II; the measured line-of-sight velocities are used to reconstruct the three Cartesian velocity components within the measured volume. The evolution of wakes and their associated deficits in wind speed are compared to CFD simulations and to predictions from a recently developed wake model [8]. Lastly, LIDAR measured wind speeds are shown to be in very good agreement with measurements from an instrumented drone [7].


A mobile-based LIDAR system that has low cost-of-ownership and is easily deployed has been developed to provide the wind industry with easier access to advanced remote sensing technology. Measurements in utility-scale wind farms demonstrate that this innovative system is well suited to improve our knowledge of flows in complex terrain, to advance the development of CFD tools, and to reduce the uncertainty in wake models.

Learning objectives
• Understand benefits of mobile-based remote sensing
• Grasp idea of operation of 3D scanning LIDAR
• Gain knowledge of methods to validate measurement systems
• Be familiar with characteristics of wind turbine wakes and differences between atmospheric flows in complex and flat terrains
• Understand novel approaches to wake modelling and microscale CFD simulations