@inproceedings{40d6a096f1e74e9ba49505b1bf9e5c66,
title = "Assessing climate change vulnerability of microgrid systems",
abstract = "In this paper, we build a framework to assess climate-change impacts on a power system. In order to appropriately capture the uncertainty of the climate change's multi-dimensional impacts, we argue that the multiple representative scenarios need to be set. Therefore, we developed a data-driven method to select representative scenarios instead of using the random-sampling method. We explain why the data-driven method is more appropriate for the research on the climate change than the random-sampling method. We adopt our framework to analyze an island nation's micro grid system. The research demonstrates that the climate change can significantly impacts this nation's electricity generation cost, energy security, and environmental performance.",
keywords = "Climate change, Generation capacity risks, Island micro grid, Vulnerability",
author = "Yang Yu and Moy, \{Kevin R.\} and Chapman, \{William E.\} and O'Neill, \{Patrick L.\} and Ram Rajagopal",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE Power and Energy Society General Meeting, PESGM 2016 ; Conference date: 17-07-2016 Through 21-07-2016",
year = "2016",
month = nov,
day = "10",
doi = "10.1109/PESGM.2016.7742061",
language = "English",
series = "IEEE Power and Energy Society General Meeting",
publisher = "IEEE Computer Society",
booktitle = "2016 IEEE Power and Energy Society General Meeting, PESGM 2016",
address = "United States",
}