Statistical load estimation using a nacelle-based lidar system

The paper presents the results of statistical load analyses based on data measured at the 5MW AREVA Wind M5000 onshore prototype. Measurements with standard meteorological measurement devices are analysed and compared to measurements with a pulsed LIDAR system which is enhanced with a multi-purpose scanning device installed on the top of the nacelle of the turbine. Based on these measurements statistical summaries of relevant meteorological parameters have been used for normative procedures to calculate the mechanical loads which occur at the wind energy turbine. It could be verified that LIDAR systems can substitute standard measurement devices for a load estimation of wind energy turbines

Model based wind vector field reconstruction from lidar data

In recent years lidar technology found its way into wind energy for resource assessment and control. For both fields of application it is crucial to reconstruct the wind field from the limited information provided by a lidar system. For lidar assisted wind turbine control model based wind field reconstruction is used to obtain signals from wind characteristics such as wind speed, direction and shears in a high temporal resolution. This work shows how these methods can be used for lidar based wind resource assessment in complex situations, where high accuracy is important, but cannot be archived by conventional technique. The reconstruction is validated for ground based lidar systems with measurement data and for floating lidar systems with detailed simulations

Lidars and wind turbine control

Reducing mechanical loads caused by atmospheric turbulence and energy optimization in the presence of varying wind are the key issue for wind turbine control. In terms of control theory changes in the inflowing wind field as gusts, varying shears and directional changes represent unknown disturbances. However, conventional feedback controllers can compensate such excitations only with a delay since the disturbance has to be detected by its effects to the turbine. This usually results in undesired loads and energy losses of wind turbines. From the control theory point of view disturbance rejection can be improved by a feedforward control if the disturbance is known. Not fully covered by theory, but used in practice is the further advantage of knowing the disturbance in the future, e.g. in chassis suspension or in daily life when vision is used to circumnavigate obstacles with a bicycle. In a similar way wind field measurements with remote sensing technologies such as Light Detection and Ranging (LIDAR) might pave the way for predictive wind turbine control strategies aiming to increase energy yield and reduce excessive loads on turbine components. Remote sensing offers wind speed tracking at various points in space and time in advance of reaching the turbine and before hitting sensors at the blades or nacelle. This provides the control and safety system with sufficient reaction and processing time

Prospects of optimization of energy production by LIDAR assisted control of wind turbines

In the presented work two approaches to increase the energy production of wind turbines are studied assuming the usage of a wind speed measurement provided by a nacelle based LIDAR system: The first approach uses the knowledge of the incoming wind speed to assist variable speed control. The second approach uses the wind direction information measured by a LIDAR system for yaw control. From this first analysis only marginal benefit can be gained by the LIDAR assisted speed control, but an increase of energy production by a couple of percent can be expected by LIDAR assisted yaw control

Determination of stationary and dynamical power curves using a nacelle-based lidar system

This paper investigates the determination of stationary and dynamical power curves using a nacelle-based lidar system. Wind speed measurements on one of the REpower 5MW turbines at the German offshore test site "alpha ventus" were carried out with a pulsed lidar system that is capable of measuring the wind field at different measurement planes over the rotor swept area. The results show that the stationary lidar-based power curve has a small scatter but is shifted towards lower wind speeds compared to a conventional power curve measured with a cup anemometer from a met mast. The new approach of calculating dynamical power curves shows short-time dynamics of the turbine and allows a quick detection of changes such as the icing of an anemometer or the reduction in the maximum power output of the wind turbine

Testing of frozen turbulence hypothesis for wind turbine applications with a scanning LIDAR system

Taylor’s frozen turbulence hypothesis is tested in its applicability for wind turbine applications. In this research full field measurements are performed at a test site for multi-megawatt wind turbines by means of a pulsed LIDAR with a scanning device. The system is installed at the top of the nacelle of a 5MW wind turbine. It provides simultaneous wind speed, with a maximum sampling rate of 5 Hz, at different stations parallel to the mean wind. Measurements in a range between 0.4 and 1.6 rotor diameter are performed following several two and three dimensional trajectories. The spectral characteristics of measurements taken simultaneously at different separation distances are studied. The scanning strategy which maximizes the wavenumber region where results are consistent with Taylor’s hypothesis is assessed. The best results are achieved by a horizontal sliding trajectory with valid wavenumbers up to 0.125 rad/m

Swabian MOSES 2021: An interdisciplinary field campaign for investigating convective storms and their event chains

The Neckar Valley and the Swabian Jura in southwest Germany comprise a hotspot for severe convective storms, causing tens of millions of euros in damage each year. Possible reasons for the high frequency of thunderstorms and the associated event chain across compartments were investigated in detail during the hydro-meteorological field campaign Swabian MOSES carried out between May and September 2021. Researchers from various disciplines established more than 25 temporary ground-based stations equipped with state-of-the-art in situ and remote sensing observation systems, such as lidars, dual-polarization X- and C-band Doppler weather radars, radiosondes including stratospheric balloons, an aerosol cloud chamber, masts to measure vertical fluxes, autosamplers for water probes in rivers, and networks of disdrometers, soil moisture, and hail sensors. These fixed-site observations were supplemented by mobile observation systems, such as a research aircraft with scanning Doppler lidar, a cosmic ray neutron sensing rover, and a storm chasing team launching swarmsondes in the vicinity of hailstorms. Seven Intensive Observation Periods (IOPs) were conducted on a total of 21 operating days. An exceptionally high number of convective events, including both unorganized and organized thunderstorms such as multicells or supercells, occurred during the study period. This paper gives an overview of the Swabian MOSES (Modular Observation Solutions for Earth Systems) field campaign, briefly describes the observation strategy, and presents observational highlights for two IOPs