Doppler Wind LiDARs for Renewable Energy - Wind Power - Energy - Wind Energy
Provides accurate 3D wind profile for wind resource survey, turbine power curve test, remote met tower scanning, wind shear analysis, complex terrain and offshore turbine wake test, pitch control, to optimize wind farm site selection and layout.
OFFSHORE WIND RESOURCE DEVELOPMENT
Programme overview
Compared with the onshore wind power, the offshore are more abundant in wind resources, weaker in wind turbulence intensity and wind shear, and less limit by the noise, landscape, birds, electromagnetic wave and other problems for wind farm construction. Therefore, offshore wind power has become the main target of wind power development in the future. The difficulties in the preliminary survey of offshore wind resources are mainly in the following aspects: adaptability to harsh marine environment, platform attitude swing, power supply, deep-sea signal transmission and maintenance. To solve these problems, Leice Transient Technology, Shandong Academy of Sciences, Ocean University of China, Pilot National Laboratory for Marine Science and Technology (Qingdao) and other key institutes have jointly developed advanced equipment for the development of offshore wind resources.
Features of the scheme
Pioneering in proposal and deployment of dia.10m large buoy to survey deep sea wind conditions. The large buoy has strong survivability and extreme weather adaptability;
Patented lidar real-time attitude correction algorithm. When the floating lidar is swaying due to sea waves, the data can be corrected in real time according to the measured buoy attitude;
Beidou communication system with data security protection, suitable for deep-sea survey;
Customized buoy power supply system, adaptable to various harsh environments, which can work continuously for more than 30 days in cloudy days;
COMPLEX TERRAIN WIND SHEAR ANALYSIS
In the preliminary assessment of wind resources, surveys, and refined site selection, the placement of lidar and power supply are issues that need to be carefully considered. The location should avoid deep valleys, cliffs and other highly turbulent terrain. Since there is usually no mains power supply during the measurement, solar cells, small wind turbines or fuel power sources are required for power supply.
According to weather conditions such as heavy fog, the integrated wind speed deep learning prediction software package of the lidar can be expanded. The lidar can continuously optimize the wind speed prediction through the method of machine learning according to the actual measured wind speed, the terrain conditions, seasons and other conditions. When the lidar’s detection range is limited due to such weather as heavy fog, the forecast data output can be adopted to ensure the data acquisition rate within the entire measurement range.
WIND POWER CURVE PREDICTION
Programme overview
The power characteristic curve of a wind turbine is the best technical index to measure the power generation capacity of a wind turbine. According to the IEC 61400-12-1 "Wind Turbine Power Characteristic Test" standard, the power curve test of a wind turbine requires the installation of a wind measurement tower in the main wind direction of the wind turbine under test. This brings certain inconvenience to the power curve test. The use of wind lidar to test the power characteristics of wind turbines not only greatly shortens the equipment installation cycle, but also facilitates the maintenance of the equipment, which is of positive significance for promoting the development of the power curve testing technology of wind turbines worldwide.
Features of the scheme
1. According to IEC61400-12-1: 2107, in flat areas, vertical wind tower type lidar can replace traditional wind measuring towers, and set up wind lidar for measurement at 2.5D place of wind turbines.
2. The power curve measurement on the sea or complex terrain requires the application of scanning lidar or special algorithms.
WIND FARM CONTROL
Programme overview
When the incoming wind passes through the rotating wind wheel, the wind speed decreases and the turbulence intensity increases downstream of the wind turbine, which is called the wake effect of the wind turbine. The wake effect has two main effects on the safe and efficient operation of wind turbines: 1) When the incoming wind speed of the wind turbine in the wake decreases, and the power of the wind turbine will decrease by 5%~40%; 2) When the turbulence intensity in the wake increases, The fatigue load of the wind turbine increases by 10% to 45%. A deep understanding of wake effects is the key to the micro-site selection of wind farms, which is of great significance for improving the efficiency and working life of wind turbines.
Features of the scheme
One unit of Wind3D 6000 can monitor the wake of a whole wind farm, reaching a scanning range of 6km in radius, which can clearly observe the turbine‘s position and the size and flow direction of the wake, as well as the wind speed and wind direction information of the environmental wind field. To avoid the wear of the wind turbine components under high wind speed, and the influence of the front wind turbine wake on the power generation of the rear wind turbine, it is necessary to control the blades movement of the wind turbine based on the lidar monitoring data.。
NETWORK WIND MEASUREMENT IN COMPLEX MOUNTAINS
Programme overview
The conventional wind profile monitoring is mainly based on multi beam inversion calculation. The premise of measurement is that the horizontal wind field is uniform, while the horizontal wind field on the underlying surface of mountainous and urban complex terrain is uneven, especially near the ground. Therefore, in the detection of complex underlying surface, complex algorithm is often used to eliminate the turbulent data. However, the virtual tower (VT) technology, based on the cooperative observation of three lidars, enables the detection of the high-altitude wind field on complex underlying surface, without the premise that the horizontal wind field is uniform.
Features of the scheme
To study the wind field structure and evolution characteristics under the influence of complex terrain and atmospheric instability conditions, Leice team and Ocean University of China carried out the cooperative observation experiment with 3units of Wind3D 6000 scanning wind lidars, and compared the collaborative observation results with vertical lidar WindMast WP350 to verify the accuracy of synchronous observation.
YAW ERROR MEASUREMENT AND CORRECTION
Programme overview
The energy of wind turbines comes from wind impellers, thus many technological transformations of wind turbines focus on improving the efficiency of wind impellers. The yaw error is a very common problem of the wind wheel efficiency. Because the wind turbine yaw is discontinuous, the error of the wind direction is not easy to be found, so the yaw error has been ignored.
Inaccurate wind measurement means loss of power generation. The error sources that affect the wind turbine yaw are:
(A) Installation error of the wind vane.
(B) Deflected airflow caused by the nacelle shape and the blades rotation.
(C) Yaw algorithm error caused by the air disturbance vortex of the blades and the nacelle.
Features of the scheme
WindHorizon H400 is a miniaturized and high-precision forward-looking wind lidar for nacelle installation, which can accurately detect the wind speed and direction information of any 10 distance gates from 50m to 400m in front of the turbine hub. The lidar shoots two laser beams into the front air of the wind turbine. By detecting the Doppler frequency shift of the reflected laser beams, the wind speed and direction of the air flow in front of the wind turbine can be measured. The wind impellers may block the laser beam because of its rotation, which WindHorizon H400 can automatically filter through advanced algorithms.