Wind Turbine Clutter Detection in Surveillance Meteorological Radar Tasks

Wind Turbine Clutter (WTC) mitigation is a challenging issue that worldwide weather services are facing at the moment. The use of wind farms to generate electricity is growing increasingly due to the importance of being a renewable energy source. These installations can have over a hundred turbines of up to 120 m height each. Moreover, windmills are expected to be significantly higher in a few years, with heights reaching 200 m. This continued growth both in the number and the height of the wind farms is seriously threatening the correct performance of weather radars.

Wind farm installations relatively near to weather radars may block the normal propagation of the radar signals and cause reflectivity clutter returns. Due to the motion of blades, with tip velocities near 90 m s-1, the standard clutter mitigation techniques fail to mitigate the effects of wind farms on radar products. Thus, this clutter and interference may cause, for instance, the misidentification of storms near wind farms; in general they cause false estimates of rain accumulation and rain Doppler velocity.

Several studies addressing the problem in C-band and S-band Doppler weather radars have been published to date, with encouraging results. Some of these studies are focused on WTC characterization, giving a better understanding of WTC physical nature and so, giving clues about its mitigation. Some others are oriented to WTC lessening in spotlight operation mode, that is, the antenna dish is stationary. These works use the unique WTC radar signature in different ways. First of all, as the time that a blade is reflecting the radar signal is small, the response in time can be averaged. Second, the distinctive flashes produced by the blades can be detected and then removed with tomographic techniques. Third, the clear periodicity shown by WTC flashes allows its detection. In operational radars, however, these techniques are useless, as the radar antenna is constantly rotating in a surveillance operation mode. Some studies propose interpolation in order to remove WTC from reflectivity and velocity PPIs, but a previous knowledge about the location of wind turbines is required. A fixed wind turbine clutter map has two main disadvantages. First, wind farms can occupy more than 50 km long where inter-turbine distances can be smaller or not than the radar range resolution. This can cause an important lost of valuable weather information. Second, wind turbines are not always running. The blades only move when the velocity of the wind is appropriate for energy production. Then, on-the-go detection is highly more efficient for weather data accuracy.

In this work a holistic approach to wind turbine clutter detection and mitigation is performed. The detection is based on feature extraction. Although the technique is employed in surveillance operation mode, the experience with spotlight data will be used, as it provides the information about the behavior of WTC in time. Then, several parameters will be used as indicators of WTC presence in radar data: abrupt reflectivity differences between adjacent range and azimuth bins, large Doppler shifts, micro-Doppler modulation and periodicities will be measured and categorized. Both simulated and recorded radar data from clutter and weather will be used for this purpose. After detection, interpolation techniques will be employed to subtract WTC from the weather data. The interpolation method must assure the continuity of weather data as well as its integrity.