Abstract
Coherent wind doppler lidar (CWDL) is a cost-effective way to estimate wind power potential at hub height without the need to build a meteorological tower. However, fog and low stratus (FLS) can have a negative impact on the availability of lidar measurements. Information about such reductions in wind data availability for a prospective lidar deployment site in advance is beneficial in the planning process for a measurement strategy. In this paper, we show that availability reductions by FLS can be estimated by comparing time series of lidar measurements, conducted with WindCubes v1 and v2, with time series of cloud base altitude (CBA) derived from satellite data. This enables us to compute average maps (2006–2017) of estimated availability, including FLS-induced data losses for Germany which can be used for planning purposes. These maps show that the lower mountain ranges and the Alpine regions in Germany often reach the critical data availability threshold of 80% or below. Especially during the winter time special care must be taken when using lidar in southern and central regions of Germany. If only shorter lidar campaigns are planned (3–6 months) the representativeness of weather types should be considered as well, because in individual years and under persistent weather types, lowland areas might also be temporally affected by higher rates of data losses. This is shown by different examples, e.g., during radiation fog under anticyclonic weather types.
Highlights
Wind turbine planning requires reliable estimation of the wind power potential at a prospective site which necessitates knowledge of the wind conditions
The algorithm uses a random forest machine learning model trained with cloud base altitudes measured by synoptic weather observation data (SYNOP) and Meteorological Aviation Routine Weather Reports (METAR) stations and the pixel information from the satellite data corresponding to these station locations to predict cloud base altitudes
10-min availability is below the 80% threshold in the cloud base altitudes (CBA) ≤ 100 m case
Summary
Wind turbine planning requires reliable estimation of the wind power potential at a prospective site which necessitates knowledge of the wind conditions. The optimal hub height depends on the type of the wind turbine, the wind regime at the location, and the economic costs and benefits with regard to different planning scenarios [4,5]. The trend for the generation of turbines goes up to 160 m hub heights and will most likely increase up to 180 m in the future [6]. It is of the utmost importance for planning and financing of wind parks at a certain position that the wind situation at Energies 2020, 13, 3859; doi:10.3390/en13153859 www.mdpi.com/journal/energies
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