Search Results

You are looking at 1 - 10 of 72,530 items for :

  • Refine by Access: All Content x
Clear All
A. Sathe
,
J. Mann
,
J. Gottschall
, and
M. S. Courtney

1. Introduction A theoretical model is developed to estimate the systematic errors in the second-order moments of wind speeds in the atmospheric surface layer measured by lidars. The systematic errors are those that arise resulting from the averaging effect in the sample or pulse volume and the relatively large circle in which Doppler lidars scan to obtain two-component horizontal wind profiles. Two types of lidars are considered, the ZephIR, developed by QinetiQ (Natural Power), as a

Full access
Yvonne Käsler
,
Stephan Rahm
,
Rudolf Simmet
, and
Martin Kühn

1. Measurement technique Lidar is a remote sensing technique that transmits a laser beam into the atmosphere and the backscattered light is detected. The pulsed Doppler wind lidar, which was used for the measurements in Bremerhaven, Germany, takes advantage of the fact that the center frequency of the received laser pulses is shifted compared to the outgoing pulses because of the Doppler effect, which occurs from backscattering on moving particles. This shift in frequency provides information

Full access
Andreas Rettenmeier
,
David Schlipf
,
Ines Würth
, and
Po Wen Cheng

1. Introduction Different certification procedures in wind energy—for example, power performance testing or load estimation—require measurements of the wind speed. Nowadays, such wind speed data are usually obtained using anemometers installed on a meteorological mast. Increasing hub heights and rotor diameters also increase wind shear effects on the loading and the electrical power output of a wind turbine. One promising method of taking the shear effect into account is the use of an

Full access
Merete Badger
,
Alfredo Peña
,
Andrea N. Hahmann
,
Alexis A. Mouche
, and
Charlotte B. Hasager

1. Introduction Ocean wind retrieval from active microwave sensors on board satellites has been feasible since the early 1990s, when empirical relationships were established between observations of radar backscatter from the sea surface and winds at the height of 10 m ( Stoffelen and Anderson 1993 ). Since then, the archives of both satellite observations and offshore in situ data have grown, and the geophysical model functions (GMFs) used for wind retrieval have been validated and improved

Full access
Jake Badger
,
Helmut Frank
,
Andrea N. Hahmann
, and
Gregor Giebel

1. Introduction A wind atlas is a geospatial dataset containing information about the wind climate that can be used to determine wind power resources at wind turbine sites. A wind atlas, typically covering 10 4 –10 6 km 2 , describes direction-sector-dependent wind speed distributions at a number of different heights above ground level (AGL) and a number of surface roughness types. A wind atlas can be derived from observations; however, where there is an insufficiently dense network of high

Full access
David Schlipf
,
Po Wen Cheng
, and
Jakob Mann

1. Introduction Lidar systems are able to provide information about the wind field approaching a wind turbine in advance, which can be used to assist wind turbine control. This field of investigations has increased significantly in recent years, and several controllers for load reduction or energy yield increase have been tested in simulations (see, e.g., Laks et al. 2010 ; Dunne et al. 2012 ; Schlipf et al. 2013b ; Koerber and King 2011 ; Henriksen 2011 ; Kragh et al. 2013 ). The latest

Full access
Jacob Berg
,
Nikola Vasiljevíc
,
Mark Kelly
,
Guillaume Lea
, and
Michael Courtney

1. Introduction Conventionally, winds in the atmospheric boundary layer are measured by mast-mounted cup or sonic anemometers. Today this picture is heavily challenged by remote sensing instruments, such as sodars and especially lidars ( Emeis et al. 2007 ). Whereas the mast-mounted instruments (mainly sonics) are still superior when it comes to measuring and quantifying turbulent structures ( Sathe et al. 2011 ), the advantages of remote sensing instruments are obvious: easy deployment for

Full access
Sicheng Wu
and
Cristina L. Archer

1. Introduction Wind turbines extract energy from the wind and generate wakes, which are plume-like volumes of low wind speed that form downstream of a turbine. The upper parts of the wakes are also characterized by high turbulent kinetic energy (TKE) and high turbulent fluxes, which cause enhanced vertical mixing above hub height. Vertical mixing significantly impacts the vertical temperature and moisture distribution around the rotor area. For example, at night under stable conditions with

Full access
Brian D. Hirth
and
John L. Schroeder

1. Introduction Wind turbine wakes are partly responsible for what is commonly referred to as the “underperformance” of wind farms by 10%–20% ( Barthelmie et al. 2007 , 2009 , 2010 ; Barthelmie and Jensen 2010 ; Schepers et al. 2012 ), in part attributed to shortcomings in the current power-output models to accurately replicate turbine wakes and modulated flow fields throughout a wind farm. Wakes represent an extraction of energy from the free streamflow that may become inflow for a

Full access
Alfredo Peña
,
Sven-Erik Gryning
,
Jakob Mann
, and
Charlotte B. Hasager

1. Introduction The mixing-length concept attributed to Prandtl (1925) has been a successful tool to describe the mean wind speed profile within the surface layer—the lowest 10% of the atmospheric boundary layer (ABL)—in neutral conditions as shown in Panofsky and Petersen (1972) and Carl et al. (1973) , leading to the well-known logarithmic wind speed profile. The correction to the logarithmic wind speed profile due to diabatic conditions introduced in Monin–Obukhov similarity theory can

Full access