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Optimization of Distributed Generation Investment Planning by Climate Region

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dc.contributor.advisor McGarity, Arthur
dc.contributor.author Dahmm, Hayden Wallace
dc.date.accessioned 2015-08-05T18:28:00Z
dc.date.available 2015-08-05T18:28:00Z
dc.date.issued 2015-05
dc.identifier.uri http://hdl.handle.net/10066/16618
dc.description.abstract Distributed Generation (DG) will be an important feature of carbon mitigation policies, and understanding the limitations on generator investment will help form more effective policy options. This study explored the tradeoff between carbon dioxide emissions and the capital invested into DG for different climates of the United States. The multi-objective evolutionary algorithm Borg was combined with load and generator profiles produced by GridLab-D to estimate the combinations of DG that can reduce carbon emissions in the most cost effective ways possible. Results suggest that there are diminishing returns on DG investment, so the ability to reduce emissions decreases with higher investments. An interpretation of non-dominated solution sets shows that the West Coast climate should have a strong policy preference for solar collectors, while the Southeast Coastal climate should have a strong policy preference for small wind turbines. Moreover, a portfolio investment approach is preferred, but optimal technology combinations are potentially sensitive to changes in technology prices. This analysis should be repeated in greater detail and applied to a wider range of climates and communities. en_US
dc.description.sponsorship Swarthmore College. Dept. of Engineering en_US
dc.language.iso en_US en_US
dc.rights Full copyright to this work is retained by the student author. It may only be used for non-commercial, research, and educational purposes. All other uses are restricted.
dc.title Optimization of Distributed Generation Investment Planning by Climate Region en_US
dc.type Thesis (B.A.)


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