• DocumentCode
    2368468
  • Title

    Power consumption scheduling for residential buildings

  • Author

    Mangiatordi, Federica ; Pallotti, Emiliano ; Vecchio, Paolo Del ; Leccese, Fabio

  • Author_Institution
    Electron. Dept., Univ. of Roma TRE, Rome, Italy
  • fYear
    2012
  • fDate
    18-25 May 2012
  • Firstpage
    926
  • Lastpage
    930
  • Abstract
    The increasing growth of electricity usage in buildings points out the significant role of residential users in the programs for the efficient control and management of electrical energy. The shaving of consumption peaks in household is becoming an integral part of the national energy strategies to reduce the risk of blackouts and ensure environmental sustainability of new urban context. This paper investigates the use of the paradigm of swarm intelligence to scheduling the operation of household appliances in order to reduce to smooth the variation and reduce the peak-to-average ratio of total electricity demand at home. Simulation results confirm the proposed approach.
  • Keywords
    building management systems; energy consumption; particle swarm optimisation; sustainable development; electrical energy control; electrical energy management; electricity demand; electricity usage; environmental sustainability; household appliance operation scheduling; power consumption scheduling; residential buildings; swarm intelligence; Buildings; Electricity; Home appliances; Optimization; Particle swarm optimization; Peak to average power ratio; Smart grids; Energy management; Smart grid; power consumption scheduling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Environment and Electrical Engineering (EEEIC), 2012 11th International Conference on
  • Conference_Location
    Venice
  • Print_ISBN
    978-1-4577-1830-4
  • Type

    conf

  • DOI
    10.1109/EEEIC.2012.6221508
  • Filename
    6221508