Offshore wind simulations were performed with the Weather Research and Forecasting (WRF) model driven by three different sea surface temperature (SST) datasets for Japanese coastal waters to investigate the effect of the SST accuracies on offshore wind simulations. First, the National Centers for Environmental Prediction Final analysis (FNL) (1°× 1°grid resolution) and the Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) (0.05°× 0.05°grid resolution) datasets were compared with in situ measurements. The results show a decrease in accuracy of these datasets toward the coast from the open ocean. Aiming at an improved accuracy of SST data, we developed a new high-resolution SST dataset (0.02°× 0.02°grid resolution). The new dataset referred to as MOSST is based on the Moderate Resolution Imaging Spectroradiometer (MODIS) product, provided by the Japan Aerospace Exploration Agency (JAXA). MOSST was confirmed to be more accurate than FNL and OSTIA for the coastal waters. Then, WRF simulations were carried out for 1 year with a 2 km grid resolution and by using the FNL, OSTIA and MOSST datasets. The use of the OSTIA dataset for a WRF simulation was found to improve the accuracy when compared with the FNL dataset, and further improvement was obtained when the MOSST dataset was applied. The sensitivity of wind speed and wind energy density to SST is also discussed. We conclude that the use of an accurate SST is a key factor not only for realistic offshore wind simulations near the surface but also for accurate wind resource assessments at the hub height of wind turbines. Published online in Wiley Online Library (wileyonlinelibrary.com).
In recent years, there has been a rapid development of the wind farms in Japan. It becomes very important to investigate the wind turbine arrangement in wind farm, in order that the wake of one wind turbine does not to interfere with the flow in other wind turbines. In such a case, in order to achieve the highest possible efficiency from the wind, and to install as many as possible wind turbines within a limited area, it becomes a necessity to study the mutual interference of the wake developed by wind turbines. However, there is no report related to the effect of the turbulence intensity of the external flow on the wake behind a wind turbine generated in the wind tunnel. In this paper, the measurement results of the averaged wind profile and turbulence intensity profile in the wake in the wind tunnel are shown when the turbulence intensity of the external wind was changed. The wind tunnel experiment is performed with 500mm-diameter two-bladed horizontal axis wind turbine and the wind velocity in wake is measured by an I-type hot wire probe. As a result, it is clarified that high turbulence intensities enable to the entrainment of the main flow and the wake and to recover quickly the velocity in the wake.
A wind measurement campaign using a single scanning light detection and ranging (LiDAR) device was conducted at the Hazaki Oceanographical Research Station (HORS) on the Hazaki coast of Japan to evaluate the performance of the device for coastal wind measurements. The scanning LiDAR was deployed on the landward end of the HORS pier. We compared the wind speed and direction data recorded by the scanning LiDAR to the observations obtained from a vertical profiling LiDAR installed at the opposite end of the pier, 400 m from the scanning LiDAR. The best practice for offshore wind measurements using a single scanning LiDAR was evaluated by comparing results from a total of nine experiments using several different scanning settings. A two-parameter velocity volume processing (VVP) method was employed to retrieve the horizontal wind speed and direction from the radial wind speed. Our experiment showed that, at the current offshore site with a negligibly small vertical wind speed component, the accuracy of the scanning LiDAR wind speeds and directions was sensitive to the azimuth angle setting, but not to the elevation angle setting. In addition to the validations for the 10-minute mean wind speeds and directions, the application of LiDARs for the measurement of the turbulence intensity (TI) was also discussed by comparing the results with observations obtained from a sonic anemometer, mounted at the seaward end of the HORS pier, 400 m from the scanning LiDAR. The standard deviation obtained from the scanning LiDAR measurement showed a greater fluctuation than that obtained from the sonic anemometer measurement. However, the difference between the scanning LiDAR and sonic measurements appeared to be within an acceptable range for the wind turbine design. We discuss the variations in data availability and accuracy based on an analysis of the carrier-to-noise ratio (CNR) distribution and the goodness of fit for curve fitting via the VVP method.
An offshore wind measurement campaign using vertical light detection and ranging (LiDAR) devices was conducted at the Hazaki Oceanographic Research Station (HORS) as part of an investigation into determining the optimal distance from the coast for a nearshore wind farm from a meteorological perspective. The research platform was a 427 m long pier located on a rectilinear coastline on the Pacific coast of the central Honshu Island in Japan. The relationship between the ratios of the increase of wind speed near the surface and fetch length within 5 km of the coast was analyzed via LiDAR observations taken at heights from 40 to 200 m. The results showed that the speed of the coastal wind blowing from land to sea gradually increased as the fetch length increased, by approximately 15–20% at 50 m above sea level around a fetch length of 2 km. Moreover, empirical equations were derived by applying the power law to the relationship between the increase of wind speed and fetch lengths at 1–5 km, as obtained from the LiDAR measurements. It was also found that the wind speed increase at a 2 km fetch length was equivalent to the effect of a 50–90 m vertical height increase on the coast in this region.
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