• DocumentCode
    2605700
  • Title

    A multi-objective optimization model of power generation with fuel and emission minimized

  • Author

    Zhuang, Chu ; Wei, Cai Guo

  • Author_Institution
    Coll. of Electr. Eng., Northeast Dianli Univ., Jilin, China
  • fYear
    2009
  • fDate
    6-7 April 2009
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Real power generation dispatch and scheduling become a kind of multi-objective decision problems when fuel costs and emission are needed to be minimized simultaneously. These objectives are usually conflicting. Based on the concept of ideal point, generation dispatch model and generation scheduling model with fuel and emission minimized simultaneously are formulated. It is accomplished by constructing a hyperspace. In the hyperspace, the dimension number of which is that of the goals to be optimized, different coordinates of a space point are of such realistic meanings as costs or emission quantities. Not only the non-commensurable and conflicting problems of different goals could be dealt with, the conclusions also could give us useful insights into the multi-objective real power optimization problems by analyzing the necessary conditions of these models are discussed. These conditions are also helpful when solving these ideal point method models.
  • Keywords
    environmental management; power generation dispatch; power generation scheduling; multiobjective decision problems; multiobjective optimization model; power generation dispatch; power generation scheduling; Constraint optimization; Cost function; Dispatching; Fuels; Mathematics; Pollution; Power generation; Power generation dispatch; Power generation economics; Power system modeling; Power system economics; environmental factors; modeling; power generation dispatch; power generation scheduling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Sustainable Power Generation and Supply, 2009. SUPERGEN '09. International Conference on
  • Conference_Location
    Nanjing
  • Print_ISBN
    978-1-4244-4934-7
  • Type

    conf

  • DOI
    10.1109/SUPERGEN.2009.5348339
  • Filename
    5348339