Economic, Climate Change, and Air Quality Analysis of Distributed Energy Resource Systems . Omu, A., Rysanek, A., Stettler, M., & Choudhary, R. Procedia Computer Science , 51:2147 - 2156, 2015. International Conference On Computational Science, \ICCS\ 2015Computational Science at the Gates of Nature
Economic, Climate Change, and Air Quality Analysis of Distributed Energy Resource Systems  [link]Paper  doi  abstract   bibtex   
Abstract This paper presents an optimisation model and cost-benefit analysis framework for the quantification of the economic, climate change, and air quality impacts of the installation of a distributed energy resource system in the area surrounding Paddington train station in London, England. A mixed integer linear programming model, called the Distributed Energy Network Optimisation (DENO) model, is employed to design the optimal energy system for the district. \DENO\ is then integrated into a cost-benefit analysis framework that determines the resulting monetised climate change and air quality impacts of the optimal energy systems for different technology scenarios in order to determine their overall economic and environmental impacts.
@article{Omu20152147,
title = "Economic, Climate Change, and Air Quality Analysis of Distributed Energy Resource Systems ",
journal = "Procedia Computer Science ",
volume = "51",
number = "",
pages = "2147 - 2156",
year = "2015",
note = "International Conference On Computational Science, \{ICCS\} 2015Computational Science at the Gates of Nature ",
issn = "1877-0509",
doi = "http://dx.doi.org/10.1016/j.procs.2015.05.487",
url = "http://www.sciencedirect.com/science/article/pii/S1877050915012958",
author = "Akomeno Omu and Adam Rysanek and Marc Stettler and Ruchi Choudhary",
keywords = "Distributed Energy Resource Systems",
keywords = "MILP",
keywords = "Air Quality",
keywords = "Optimisation ",
abstract = "Abstract This paper presents an optimisation model and cost-benefit analysis framework for the quantification of the economic, climate change, and air quality impacts of the installation of a distributed energy resource system in the area surrounding Paddington train station in London, England. A mixed integer linear programming model, called the Distributed Energy Network Optimisation (DENO) model, is employed to design the optimal energy system for the district. \{DENO\} is then integrated into a cost-benefit analysis framework that determines the resulting monetised climate change and air quality impacts of the optimal energy systems for different technology scenarios in order to determine their overall economic and environmental impacts. "
}

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