An Offshore Wind Resource Assessment and a Look into Model Errors in Wind Forecasts
Corkum, Matthew Brenton
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This dissertation will look at 3 related, but different topics. The rst, is a VHF wind proler network in Southern Ontario and Quebec, the OQnet that provides real time wind measurements from 500m - 12000m. This study will look at ways of validating the data from these prolers and comparing them to forecast models such as the Canadian GEM model in Chapter 2. The second part of this thesis will look at offshore wind resource assessment. Wind energy is a clean and viable alternative to burning fossil fuels for energy and is being expanded all over the world. Europe is a global leader when it comes to wind energy and they have expanded this industry to include many offshore wind farms. As Canada looks to accelerate their wind energy production, companies have begun to study the offshore wind resource in the Great Lakes. In 2010, Toronto Hydro started a 2 year wind resource campaign. The lidar installed by Toronto Hydro measured wind speed and direction up to hub height over a 2 year period but there were many gaps in the record. Other instruments, installed by the York University team measured platform level winds and other weather variables. Using a combination of lidar extrapolation and platform level winds a continuous series of hub height winds has been generated which is discussed in Chapter 3. Chapter 4 looks at using these data to look at Measure, Correlate, Predict (MCP) estimations of long term wind speed. Chapter 5 looks at Annual Energy Production (AEP) estimates for two potential wind farm designs for the Toronto Hydro site. Finally in Chapter 6, this dissertation looks at issues related to wind forecasting for these wind farms and what kind of errors are associated with wind energy forecasts.