• Title of article

    Multi-class appliance scheduling for cost-effective energy management with constraint and user preferences

  • Author/Authors

    Ali Khan ، M. F. Department of Electronics and Communication Engineering - Sri Sivasubramaniya Nadar College of Engineering , Chandramani ، P. V. Department of Electronics and Communication Engineering - Sri Sivasubramaniya Nadar College of Engineering

  • From page
    3257
  • To page
    3272
  • Abstract
    For decades, the electrical power grid worldwide has transformed from traditional to the smart power grid, focusing on its transparency to both utility and consumer. The energy management systems play a substantial part in demand response within the smart power grid umbrella, enabling demand-side management at the residential level. These systems generate the consumption profile of appliances and reduce the burden on end-user in scheduling appliances operations. With these consumption profiles of past usage, there is a possibility to generate a time window containing user preferable time slots for appliance operation for the next day. Using this time window, one can generate a cost-effective schedule-pattern autonomously. In this regard, this article proposes a home energy-demand management scheme consisting of a time window generator and a schedule-pattern generator to generate a cost-effectively comfortable schedule-pattern with demand threshold constraint. Multi-class appliances home enabled with a net-meter demonstrate the proposed approach’s effectiveness. The simulation results showcase that the proposed approach helps the user to save electricity bills with constraint preserving comfort.
  • Keywords
    ANN , home energy management , multi , class appliance , net , meter , pattern , generation algorithm , user comfort
  • Journal title
    Scientia Iranica(Transactions D: Computer Science and Electrical Engineering)
  • Journal title
    Scientia Iranica(Transactions D: Computer Science and Electrical Engineering)
  • Record number

    2746883