|Item type||Location||Call number||Copy||Status||Date due|
|BOOK||Mesa Lab||TJ820 .Oz99 2011 (Browse shelf)||1||Available|
A Dissertation submitted to The Faculty of The School of Engineering and Applied Science of the George Washington University in partial fulfillment of the requirements for the degree of Doctor of Philosophy
Dissertation directed by Michael R. Duffey.
After twenty years of rapidly expanding worldwide capacity and technical advance, proponents claim that offshore wind technology is commercially competitive, especially at high wind resources sites. However, the profitability of offshore projects depends on many uncertain parameters, some of them highly site specific. This uncertainty comes partly from natureal variations such as wind speed, and unknown costs of different physical system elements and their interactions. But these physical cost uncertainties are coupled with many other project-level financial factors that are not well characterized in publicly available financial assessment methodologies. Most methods use fixed design assumptions that ignore optimization for site-specific conditions. They also ignore the impacts of complex financing alternatives, lengthy project schedules, site specific emission avoidance and its monetization, and actual revenues and penalty costs in the context of site specific deregulated power networks and competitive bidding. After reviewing the evolution of cost and engineering design models for offshore wind, a prototype software tool called OFWIC - Offshore Wind Integrated Cost Model was built and tested. It is a comprehensive system model that analyzes the cost of energy under uncertainty. It is also a multidisciplinary design optimization tool that includes nested optimization algorithms to discover the most economically viable system design. The dissertation explains in detail the methodology used in OFWIC and its application in a case study for the site of the first proposed offshore wind project in the U.S. Significant variations in "cost of energy" estimates were found depending on which factors are included in the model.