1235671 (Kelly).This research has two major tasks. The first is to advance offshore wind siting methods by creating a new multi-criteria assessment framework that integrates life cycle assessment (LCA), geographic information systems (GIS), viewshed modeling, aquatic ecology, and economics to analyze the consequences of design, policy, and engineering decisions of offshore wind farm siting. By accomplishing this task, offshore wind siting assessment can integrate the many competing siting objectives within a cohesive evaluation environment, and a general methodology will be developed for site evaluation. The second task is to apply this multi-criteria methodology to the Great Lakes region to explore how offshore wind farm siting locations will impact the electric sector, environmental quality (through emissions reductions and aquatic life impacts), and local viewsheds. The completion of this task will inform the development of policy and technology with respect to offshore wind turbines, and will provide tools for conducting these analyses. The research effort will develop multi-criteria analyses that use GIS, LCA, and optimization methods to analyze and visualize the economic, environmental, and social impacts of siting offshore wind turbines. This model will incorporate data from numerous sources, much of which is geographically unique (topography, bathymetry, wind resource, population, demographics, food web), but the methods will be applicable to any location. The integration and optimization of the economic, environmental, and social impacts is a unique contribution to research in offshore wind. It allows the simultaneous evaluation of these potentially disparate objectives, and creates a means of identifying the tradeoffs that exist between them. One globally identified challenge facing humanity is the reduction of greenhouse gasses from the energy sector. Offshore wind represents a tremendous resource, but the planning and deployment of offshore wind turbines has been met with much social resistance. A more thorough and holistic approach to wind site analysis may reduce such resistance and thereby streamline offshore wind siting. This research will create a methodology for evaluating and supporting offshore wind farm siting and development that better accounts for economic, social, and environmental impacts. The multi-criteria assessment framework will be applied to a siting project in Michigan, but the methodology will be applicable to other offshore wind developments, and will enhance the understanding of tradeoffs associated with offshore wind farms to key stakeholders (e.g., local communities, developers, government agencies, investors). A teaching module on integrated assessment of offshore wind siting will be developed and tested in two Master's courses for the UM School of Natural Resources and Environment, and then refined for widespread dissemination through the UM Center for Sustainable Systems website. A professionally developed podcast or video short will be produced, posted to social media sites for broad educational impacts from K to grey, and provided to the Great Lakes Wind Collaborative for dissemination. The educational impact of this project includes both graduate and undergraduate students through independent research and course module integration. A PhD student will work on advanced GIS research for offshore wind siting which will include electricity grid and environmental modeling. This project will also leverage the UM Undergraduate Research Opportunity Program to engage undergraduates from numerous diverse backgrounds and cultures. The research team will use the research findings to update and create Wikipedia pages on topics such as ?offshore wind power?, ?electricity from wind?, and other relevant topics. This research will be accomplished by an interdisciplinary team that leverages expertise from several different and complementary communities including mechanical engineering and optimization, LCA, environmental economics, aquatic ecology and GIS.
Advancing Offshore Wind Power Sitting through Multi-criteria Assessment Integration