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Abstract:

Offshore wind farm (OWF) siting is crucial in determining the success of wind energy projects relative to multiple objectives, including increasing energy generation, decreasing installation costs, reducing life-cycle environmental impacts, displacing pollutant emissions, and reducing visual impact of wind turbines. This study examines the performance across these objectives for twenty siting scenarios in four Great Lakes counties and at various offshore distances. To evaluate wind energy potential of remote sites using wind-speed profiles, the shape parameter of the Weibull distribution of wind speeds at known weather stations was extrapolated using geostatistical kriging (Ch. 2). The best estimate of the shape parameters at candidate OWF locations varied from 1.73 to 1.82, indicating that the commonly used value of 2 may over-estimate the wind speed distribution at wind speeds that wind turbines can generate electricity.

Life-cycle environmental impacts of OWFs were evaluated using a process-based life cycle assessment for a 100 x 3MW OWF at twenty sites (Ch.3). The OWF manufacture, transportation, installation, use phase, and decommissioning indicate that, on average, one kWh of delivered electricity from OWFs will lead to global warming potential (GWP), acidification potential (AP), and cumulative energy demand (CED) impacts of 36 g CO₂eq, 0.012 mole H+eq, and 0.14 kWh fossil fuel, respectively. The environmental benefits for the same OWF scenarios are also evaluated by considering the displaced air pollutant emissions from using wind energy (Ch. 5). The monetized net benefit values for the avoided emissions ranges from $105 to $773 million, depending on the OWF locations and on the renewable energy and pollution policy mechanism.

Another OWF externality resulting from negative visual impacts was characterized and valued by combining viewshed simulation with estimates of willingness to pay data for moving wind turbines farther offshore (Ch. 4). The results show that the magnitude of visually impacted areas and population, and the monetized external cost of visual impact, decreased with increasing distance offshore and it depended on the turbine dimensions, OWF locations, population density and distribution, coastline trend, and terrain.

Finally, an integrated assessment of OWF siting investigated the trade-offs between four objectives: energy, economy, environment, and society. The multiple criteria decision analysis with subjective weighting, objective weighting and monetization approaches are compared to illustrate different preferences and values toward OWF objectives (Ch. 6). The main findings are 1) the net monetized values of twenty siting scenarios with 300 MW wind turbines over a 20 year period are determined mainly by almost equally important objectives in energy benefits (averagely $1.2 billion) and installation cost (averagely -$1.2 billion), followed by net environmental benefits (between $0.1 billion to $0.7 billion), and lastly by external cost of visual impact (averagely -$4 million); 2) one of the weighting methods (weights energy, economic, environmental, and social objectives as 40%, 40%, 10% and 10%, respectively) is more representative than other six weighting methods and four monetization approaches because it has higher correlation with other weighting and monetization methods in performance rankings of siting scenarios; 3) small changes in the offshore distance of OWFs can cause significant differences in net benefit values; and 4) renewable energy certificates (RECs) are the most effective mechanism to increase environmental benefits and promote the development of OWFs considering the overall benefits to society.

The results of this study are expected to provide more diversified information of wind energy projects for stakeholders and decision makers. Meanwhile, the findings can inform wind-energy-related policy in order to maximize the benefits of OWFs to the society as a whole.

Doctoral Committee:

Professor Gregory A. Keoleian, Co-Chair

Professor Daniel G. Brown, Co-Chair

Professor Michael R. Moore

Professor Ian A. Hiskens

Assistant Research Scientist Jarod C. Kelly