• DocumentCode
    1885697
  • Title

    A Stackelberg Game Approach to maximise electricity retailer´s profit and minimse customers´ bills for future smart grid

  • Author

    Meng, Fan-Lin ; Zeng, Xiao-Jun

  • Author_Institution
    Sch. of Comput. Sci., Univ. of Manchester, Manchester, UK
  • fYear
    2012
  • fDate
    5-7 Sept. 2012
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    This paper proposes a Stackelberg Game Approach to trade-off between maximising the profit of the retailer and minimising the payment bills of the customers. The electricity retailer determines the retail price and sends the price information to customers through an advanced metering infrastructure. According to the announced price, the customers obtain the optimal scheduling details of the appliances in each household through an optimal residential electricity consumption scheduling framework. Once the scheduling details of appliances in each household are obtained, the retailer can maximise its profit by solving the profit maximisation problem. We model the interactions between the retailer and electricity customers as a 1-leader, N-follower Stackelberg Game. At the leader´s side, i.e., for the retailer, we use genetic algorithms to maximise the profit while at the followers side, i.e., for customers, we use linear programming techniques (Simplex Method) to optimise the payment bills. Simulation results show the feasibility of the proposed approach.
  • Keywords
    electricity supply industry; game theory; genetic algorithms; linear programming; power meters; pricing; smart power grids; 1-leader n-follower Stackelberg game; advanced metering infrastructure; customer payment bills minimisation; electricity retailer profit maximisation; future smart grid; genetic algorithms; household appliances; linear programming techniques; optimal residential electricity consumption scheduling; optimal scheduling; price information; retail price; retailer profit; Companies; Genetics; Heating; Helium; Lead; Ovens; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence (UKCI), 2012 12th UK Workshop on
  • Conference_Location
    Edinburgh
  • Print_ISBN
    978-1-4673-4391-6
  • Type

    conf

  • DOI
    10.1109/UKCI.2012.6335772
  • Filename
    6335772