A review of progress and applications of pulsed doppler wind LiDARs

Doppler wind LiDAR (Light Detection And Ranging) makes use of the principle of optical Doppler shift between the reference and backscattered radiations to measure radial velocities at distances up to several kilometers above the ground. Such instruments promise some advantages, including its large scan volume, movability and provision of 3-dimensional wind measurements, as well as its relatively higher temporal and spatial resolution comparing with other measurement devices. In recent decades, Doppler LiDARs developed by scientific institutes and commercial companies have been well adopted in several real-life applications. Doppler LiDARs are installed in about a dozen airports to study aircraft-induced vortices and detect wind shears. In the wind energy industry, the Doppler LiDAR technique provides a promising alternative to in-situ techniques in wind energy assessment, turbine wake analysis and turbine control. Doppler LiDARs have also been applied in meteorological studies, such as observing boundary layers and tracking tropical cyclones. These applications demonstrate the capability of Doppler LiDARs for measuring backscatter coefficients and wind profiles. In addition, Doppler LiDAR measurements show considerable potential for validating and improving numerical models. It is expected that future development of the Doppler LiDAR technique and data processing algorithms will provide accurate measurements with high spatial and temporal resolutions under different environmental conditions

Recommendation on use of wind lidars

The 15 Early Stage Researchers (ESRs) in the LIKE project investigate topics in which wind lidar play a significant role. This report provides the ESRs an introductory reading and gives a short introduction into the basic principles, as well as an overview on the practical application of lidar wind measurement technology for a wide range of research fields, including a corresponding literature review. Wherever possible, it will also give the ESRs recommendations on the use of lidars and related best practices and provide corresponding state-of-the-art documents in the attachment.publishedVersio

A review of turbulence measurements using ground-based wind lidars

A review of turbulence measurements using ground-based wind lidars is carried out. Works performed in the last 30 yr, i.e., from 1972–2012 are analyzed. More than 80% of the work has been carried out in the last 15 yr, i.e., from 1997–2012. New algorithms to process the raw lidar data were pioneered in the first 15 yr, i.e., from 1972–1997, when standard techniques could not be used to measure turbulence. Obtaining unfiltered turbulence statistics from the large probe volume of the lidars has been and still remains the most challenging aspect. Until now, most of the processing algorithms that have been developed have shown that by combining an isotropic turbulence model with raw lidar measurements, we can obtain unfiltered statistics. We believe that an anisotropic turbulence model will provide a more realistic measure of turbulence statistics. Future development in algorithms will depend on whether the unfiltered statistics can be obtained without the aid of any turbulence model. With the tremendous growth of the wind energy sector, we expect that lidars will be used for turbulence measurements much more than ever before

Model-based study of the five main influencing factors on the wind speed error of lidars in complex and forested terrain

Wind energy will significantly contribute to renewable power generation in the future. Much of the onshore wind energy potential is located at complex and forested sites. Remote sensing, in particular, light detection and ranging (lidar), has become a valuable technology to assess the wind resource at hub height of modern wind turbines. However, common wind profile Doppler lidars suffer from errors at complex terrain sites because of their measurement principle that assumes homogeneous flow between the measurement points. This dissertation answers the question about how well lidars measure at complex terrain sites. The five main influencing factors on the lidar error are orographic complexity, measurement height, surface roughness and forest, atmospheric stability and half-cone opening angle. Structured by five hypotheses, the impact of the different factors is analyzed in a model-based parameter study. In a novel approach, the lidar error due to orographic complexity ε is split up into the part ε_c, caused by flow curvature at the measurement points of the lidar and the part ε_s, caused by the local speed-up effects between the measurement points. This approach, e.g., allows for a systematic and complete interpretation of the influence of the half-cone opening angle φ of the lidar. It also provides information about the uncertainty of simple lidar error estimations that are based on inflow and outflow angles at the measurement points. A non-dimensional approach is chosen to ensure the transferability of the acquired results to actual applications at real-world sites. The model-based parameter study is limited to two-dimensional Gaussian hills with hill height H and hill half-width L, facilitating the possibility to cover a wide range of terrain complexities and variations of the model parameters. H/L and z/L are identified as the main scaling factors for the lidar error. With a potential flow model, the linearized flow model WEng and the RANS CFD model Meteodyn WT, three models of different complexity are used. The outcome of the study provides manifold findings that enable an assessment of the applicability of these flow models. Separating the lidar error ε into ε_c and ε_s shows that, depending on the z/L ratio, speed-up effects cause 10-30 % of the total lidar error. Therefore, a significant uncertainty must be assigned on simple lidar error estimation approaches, which are based on flow inclination angles at the measurement points and neglect this effect. Orographic complexity is found to be the major influencing factor on the lidar error. Depending on the flow model used, the lidar error is about 4-5 times larger when increasing the H/L ratio from 0.1 to 0.4. It is furthermore dependent on measurement height and reaches a maximum at a z equal to 50-60 % of the hill half-width L. Below and above the maximum point, the lidar error decreases and becomes negligible at low and high levels above ground. The height-dependence is sensitive to H/L and z/L and should be assessed before a planned measurement campaign. Opposed effects of reduced φ are found on ε_c and ε_s. This explains the small differences in the total lidar error for symmetric flows in the literature. Contrary to that, in asymmetric flow situations (e.g. forested hills), φ can significantly influence the lidar error. An adaption to the actual flow situation might reduce the lidar error, but would require a more flexible technology, such as a scanning lidar. Non-linear or detached flow effects in the lee of the steep hills, induced by high surface roughness or forest, significantly reduce the lidar error. Therefore, potential flow and linearized models should not be applied at such sites, as they generally overestimate the lidar error. In an evaluation campaign, these findings are confirmed and the best results of lidar error estimation are achieved when considering the forest in the flow model. The influence of atmospheric stability in the lidar error estimations from Meteodyn WT is significant, particularly for stable stratification. At sites where significant changes in atmospheric stability occur, the lidar error is potentially overestimated by assuming neutral stratification. The dissertation clearly shows that orographic complexity, roughness and forest characteristics, as well as atmospheric stability, have a significant influence on lidar error estimation. The choice and parameterization of flow models and the design of methods for lidar error estimation are essential to achieve accurate results. The use of a RANS CFD model in conjunction with an appropriate forest model is highly recommended for lidar error estimations in complex terrain. If atmospheric stability variation at a measurement site plays a vital role, it should also be considered in the modeling. Under certain flow conditions, the half-cone opening angle can additionally affect the magnitude of the lidar error. When planning a wind farm, an accurate estimation of the prospective lidar error should be carried out before the measurement campaign. The additional uncertainty of the lidar error correction should be assessed in this context to make a profound decision on whether a lidar measurement is feasible at the given site