Date of Award

12-2020

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Ocean Engineering and Marine Sciences

First Advisor

Prasanta Sahoo

Second Advisor

Stephen Wood

Third Advisor

Ronnal Reichard

Fourth Advisor

Jian Du

Abstract

Offshore floating wind turbines have been developed in deep water where bottom-fixed offshore wind turbines are cost-prohibitive. Gulf of Maine has one of the greatest potential wind energy on the east coast. A detailed analysis of metocean data is essential for the dynamic simulation of the floating offshore wind turbine and the offshore wind farm layout optimization. Wave scatter diagram represents the joint probability of significant wave height and peak periods. In the wind energy industry, turbulence intensity is defined as the standard deviation of the horizontal wind speed divided by the average wind speed over certain time period. Uniform flow is widely adopted in both numerical and experimental research works. However, dynamic and structural responses of the floating offshore wind turbine may have different characteristics and should be investigated. Three typical work conditions were conducted in time-domain and frequency-domain analysis. The fatigue damage, especially short-term damage equivalent loads, was compared in different turbulence intensities. The extreme response prediction of the floating wind turbine is necessary for the structural reliability. The prediction of long-term extreme responses involves quantification of extreme value distribution at very upper tail with very small exceedance probabilities. Several statistical extrapolation methods including generalized extreme value theory, peak-over-threshold method were discussed. A newly developed novel approach named average conditional exceedance rate method (ACER) could be analyzed more accurately and efficiently. Wind farm layout optimization is an important factor in the wind farm design, and it involves optimally positioning turbines in the wind farm to minimize the wake effects and maximize the power output. A newly developed Gaussian wake model was adopted, and several optimization algorithms were compared to find the most effective optimization algorithm. Penalty function method was introduced in the three-dimensional wind farm layout optimization. The performance of different optimization algorithms was investigated with several turbine densities. The result would show the best optimization algorithms in handling wind farm layout optimization problem.

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