On investigating wind-wave resource to enhance predictability in offshore wave energy deployments

Abstract

Wave resource identification affects the decision making process for the deployment of offshore infrastructure and future marine energy projects. Investigating and identifying trends in the sea state for a location of interest is somewhat difficult, the interaction between shallow and deep waters influences, significantly the viability of future installations. As wave energy is emerging as a strong candidate in renewable energy production, the necessity for assessing the wave resource of an area is even more important. The majority of offshore infrastructures is located to shallow and mid-depth seas, and although large scale numerical models can simulate open seas the identification of waves reaching these areas are less resolved and are based on approximations, due to physics limitation within the models. Numerical wave models are an important tool for the assessment of various sea states, although rigorous verification and attention to their setting up is necessary. The different interactions due to depth may alter our expected results completely if an improper setting of the model is implemented. For this work, the popular numerical software, SWAN (Simulating WAves Nearshore) has been utilised to hindcast wave conditions for Outer Hebrides in Scotland. An extensive calibration and validation has been conducted using various wind input data from different sources. The results show that a good correlation exists for wave parameters between model output and measured wave data from wave buoys.