Abstract
Abstract. For the past 2 decades wind turbines have been growing in number all over the world as a response to the increasing demand for renewable energy. However, the rapid expansion of wind turbines presents a problem for many radar systems, including weather radars. Wind turbines in the line of sight of a weather radar can have a negative impact on the radar's measurements. As weather radars are important instruments for meteorological offices, finding a way for wind turbines and weather radars to co-exist would be of great societal value.Doppler weather radars base their measurements on in-phase and quadrature phase (I/Q) data. In this work a month's worth of recordings of high-resolution I/Q data from an operational Swedish C-band weather radar are presented. The impact of point targets, such as masts and wind turbines, on the I/Q data is analysed and characterised. It is shown that the impact of point targets on single radar pulses, when normalised by amplitude, is manifested as a distinct and highly repeatable signature. The shape of this signature is found to be independent of the size, shape and yaw angle of the wind turbine. It is further demonstrated how the robustness of the point target signature can be used to identify and filter out the impact of wind turbines in the radar's signal processor.
Highlights
Wind turbines worldwide are rapidly growing in numbers to meet the increasing demand for renewable energy (Global Wind Energy Council, 2016)
The weather radar Vara is surrounded by wind turbines and masts
The first step to successfully filter the impact of wind turbines in weather radar inphase and quadrature phase (I/Q) data is to automatically identify their signature, which ideally should be possible during conditions of clear weather as well as during precipitation
Summary
Wind turbines worldwide are rapidly growing in numbers to meet the increasing demand for renewable energy (Global Wind Energy Council, 2016). Interpolating radar products may lead to unnecessarily large losses of information, and while gap-filling radars can replace contaminated measurements, they are likely a costly solution Another possible way to reduce the impact of wind turbines on weather radars is to develop filters, acting on low level data in the radars’ signal processors. In order to analyse the effect of wind turbine yaw angle (which depends on the wind direction), the local wind speed and wind direction were obtained from one of SMHI’s automatic weather stations (58.3221◦ N, 13.0406◦ E), located approximately 14 km to the northeast of the radar Vara Once every hour this station reports the average wind direction and wind speed measured during 10 min. The positions of all obstacles used in the study were confirmed visually using satellite images
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