• DocumentCode
    3124574
  • Title

    Optimizing water delivery system storage and its influence on air pollutant emission reduction

  • Author

    Jin, Steven X. ; Loya-Smalley, Carrie ; Tucker, Eric ; Qaqish, Awni ; Miller, Christopher J. ; McElmurry, Shawn P. ; Caisheng Wang

  • Author_Institution
    Tucker, Young, Jackson, Tull, Inc., Detroit, MI, USA
  • fYear
    2013
  • fDate
    27-29 June 2013
  • Firstpage
    1
  • Lastpage
    6
  • 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.
  • Keywords
    air pollution control; carbon compounds; optimisation; power generation economics; power markets; pumped-storage power stations; pumping plants; water storage; LMP data; Metro Detroit area; Michigan; air pollutant emission reduction; carbon dioxide emission reduction; electricity consumption; hourly on-duty generation type; hydraulic model; locational marginal price data; open electrical market; pollutant emission rate; pumping energy optimization; quantitative approach; real time electrical generation; water delivery system storage; Coal; Lakes; Sociology; Statistics; air pollutant; emission reduction; generation; locational marginal price (LMP); optimization; storage; water delivery;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Green Computing Conference (IGCC), 2013 International
  • Conference_Location
    Arlington, VA
  • Type

    conf

  • DOI
    10.1109/IGCC.2013.6604492
  • Filename
    6604492