• DocumentCode
    24434
  • Title

    A New Stepwise Power Tariff Model and Its Application for Residential Consumers in Regulated Electricity Markets

  • Author

    Canbing Li ; Shengwei Tang ; Yijia Cao ; Yajing Xu ; Yong Li ; Junxiong Li ; Rongsen Zhang

  • Author_Institution
    Coll. of Electr. & Inf. Eng., Hunan Univ., Changsha, China
  • Volume
    28
  • Issue
    1
  • fYear
    2013
  • fDate
    Feb. 2013
  • Firstpage
    300
  • Lastpage
    308
  • Abstract
    Stepwise power tariff (SPT), which has been put into practice, is a crucial way for energy saving and environment protecting. In this paper, a new optimal model of SPT based on residential demand response model is presented. The optimal decision is proposed to restrain high electricity consumption as well as safeguard benefits of both supply and demand sides. As a result, the objective is designed to minimize electricity consumption and constraints are taken into consideration thoroughly, including acceptable index of consumers, average price, sales profit of power providers and basic electricity demand, which serves as a foundation for smooth implement of SPT. To solve the constrained optimal problem, genetic algorithm (GA) is employed. The effectiveness of the model and algorithm is investigated and demonstrated based on real data of 300 residents by a numerical example. The study shows that the method can reduce power consumption obviously with little sacrifice of the benefits of consumers and power providers.
  • Keywords
    genetic algorithms; power consumption; power markets; power system economics; tariffs; GA; SPT; energy saving; environment protection; genetic algorithm; high electricity consumption; optimal decision; power consumption; regulated electricity markets; residential consumers; residential demand response model; stepwise power tariff model; Elasticity; Electricity; Electricity supply industry; Load management; Optimization; Power demand; Electricity markets; energy saving; stepwise power tariff;
  • fLanguage
    English
  • Journal_Title
    Power Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8950
  • Type

    jour

  • DOI
    10.1109/TPWRS.2012.2201264
  • Filename
    6238336