Wind maps from satellites cover large areas and show horizontal wind speed variations offshore in great detail. This information is an excellent supplement to mast observations, which are limited to specific points, and to model simulations, which are typically run at coarser resolution. Wind maps from satellite synthetic aperture radar (SAR) data are particularly suitable for offshore wind energy applications because they offer a spatial resolution up to 500 m and include coastal seas. In this presentation, satellite wind maps are used in combination with mast observations and numerical modeling to develop procedures and best practices for satellite based wind resource assessment offshore. All existing satellite images from the Envisat Advanced SAR sensor by the European Space Agency (2002-12) have been collected over a domain in the South China Sea. Wind speed is first retrieved from the raw satellite observations of radar backscatter from the sea surface. The backscatter is closely related to the surface wind stress and the instant wind speed. An empirical model function is applied, which describes the backscatter-to-wind relationship for the standard height 10 m above the sea surface. The satellite winds are compared against observations from a network of coastal meteorological masts. A statistical analysis is performed to estimate the wind resources. The outcome is a series of maps showing the mean wind speed, Weibull parameters, wind power density, and uncertainties. Wind variations are clearly visible across the domain; for instance sheltering effects caused by the land masses. The satellite based wind resource maps have two shortcomings. One is the lack of information at the higher vertical levels where wind turbines operate. The other is the limited number of overlapping satellite samples which can be collected due to the satellite orbit dynamics. Both challenges are addressed. A novel methodology is applied to project the satellite wind resource maps from 10 m to higher vertical levels by means of simulations from the Weather Research and Forecasting (WRF) model. Three years of WRF data – specifically the parameters heat flux, air temperature, and friction velocity – are used to calculate a long-term correction for atmospheric stability effects. The stability correction is applied to the satellite based wind resource maps together with a vertical wind profile description in order to calculate the mean wind climate at different levels up to 100 m. Time series from coarser-resolution satellite wind products i.e. the Special Sensor Microwave Imager (SSM/I) data are used to calculate the long-term temporal variability of the wind climate. This can be used to compensate for the limited number of satellite SAR samples. Altogether, the study demonstrates how a combination of several data types adds to the accuracy and the representativeness of wind resource assessment offshore.
|Title of host publication||Proceedings of China Wind Power conference (CWP 2014)|
|Number of pages||8|
|Publication status||Published - 2014|
|Event||China Wind Power Conference 2014 - Beijing, China|
Duration: 22 Oct 2014 → 24 Oct 2014
|Conference||China Wind Power Conference 2014|
|Period||22/10/2014 → 24/10/2014|