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2013 International Green Computing Conference Proceedings (2013)
Arlington, VA, USA
June 27, 2013 to June 29, 2013
ISBN: 978-1-4799-0623-9
pp: 1-6
Steven X. Jin , Tucker, Young, Jackson, Tull, Inc., Detroit, U.S.A.
Carrie Loya-Smalley , Tucker, Young, Jackson, Tull, Inc., Detroit, U.S.A.
Eric Tucker , Tucker, Young, Jackson, Tull, Inc., Detroit, U.S.A.
Awni Qaqish , Tucker, Young, Jackson, Tull, Inc., Detroit, U.S.A.
Carol J. Miller , College of Engineering, Wayne State University, Detroit, U.S.A.
Shawn P. McElmurry , College of Engineering, Wayne State University, Detroit, U.S.A.
Caisheng Wang , College of Engineering, Wayne State University, Detroit, U.S.A.
ABSTRACT
This paper presents a quantitative approach to estimating the carbon dioxide (CO2) emission reduction by optimizing water storage operations in water delivery systems. This approach uses hydraulic models of water delivery systems to perform pumping energy optimization analyses with equalization water storage and identifies real-time electrical generation types based on Locational Marginal Price (LMP) data available in open electrical markets. The real-time pollutant emission reduction has been evaluated based on hourly on-duty generation types and pollutant emission rates for different types of generation. An example is presented that applied the proposed approach to a large water delivery system in the Metro Detroit area, Michigan. The analysis results showed a daily CO2 emission reduction of 26.1 tonnes, which accounted for approximately 3% of the total CO2 emission produced by the electricity consumption for pumping water under the maximum day demand condition of 2012.
INDEX TERMS
Coal, Lakes, Sociology, Statistics
CITATION

S. X. Jin et al., "Optimizing water delivery system storage and its influence on air pollutant emission reduction," 2013 International Green Computing Conference Proceedings(IGCC), Arlington, VA, USA USA, 2013, pp. 1-6.
doi:10.1109/IGCC.2013.6604492
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