Meteorological and Oceanographic Study


mass mapsThe municipal light plant in Hull, MA, which already operates two wind turbines, has plans to install an offshore wind project. This project would consist of four turbines, totaling about 14 MW in production capacity, installed between one and two miles off Nantasket Beach. The Wind Energy Center (WEC) has undertaken a study of wind and ocean characteristics. The goal of the study is to predict long-term external conditions, including wind, waves and ocean currents, to be used in the support-structure design.

Ocean wave and current data for the Hull Offshore Project were collected by an Acoustic Doppler Profiler (ADP) located on the ocean floor near the proposed turbines. Wind data were collected using a LiDAR (Light Detection and Ranging) device located on the nearby Little Brewster Island.

Both of these devices analyze the Doppler-shifted backscatter of their emitted signal (sound and light respectively) to calculate volume-averaged particle velocities at several heights above the instrument. The ADP velocity data combined with those from a high-speed pressure sensor are used to calculate wave characteristics such as significant wave height, peak period, dominant wave direction and directional spreading.

In order to predict the range and frequency of wind turbine load conditions, it is important to develop a joint probability distribution of wind speed and wave height. The combination of wind and waves will supply the predominant loads on the wind turbine support structure. It is relevant to the fatigue-life calculations to investigate the relative frequency of each combination of wind speed and wave state. The site-specific metocean data, combined with longer-term wave data from NOAA buoy #44013 and wind data from Thompson Island, another WEC wind monitoring site in Boston Harbor, are analyzed and combine into a metocean database. This database is used to predict long-term wind and wave distributions and extreme events.

These data, the geotechnical data, and machine characteristics will be the inputs to the turbine support structure design.