Multi-Objective Optimisation of Floating Offshore Windfarms

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The drive to reduce our dependency on fossil fuels has led to rapid growth in the renewable energy sector, particularly with respect to offshore wind power. The efficacy of near-shore static wind turbines (OWTs) has been extensively demonstrated; approximately 10% of power generated in Q1 of 2019 came from offshore wind, and the UK Government seeks to increase this to 30% by 2030.Evolutionary computation has been widely applied to the design of OWT arrays. Recently, attention has moved to the design of floating offshore wind turbines (FOWTs) which can be placed in deeper water to take advantage of stronger wind conditions. This project will explore multi-objective techniques for optimising the design of FOWT arrays such that maximal benefit is achieved for the minimum possible cost and at the minimum possible environmental impact.The optimisation of static OWTs has been extensively studied. FOWT array optimisation poses a substantially more complex problem as it requires the use of a more complex model capable of incorporating the motion of the turbines. This project is an interdisciplinary collaboration between Computer Science and Mathematics, and would suit a candidate from either background.