• DocumentCode
    667010
  • Title

    A Fuzzy Logic tool for household electrical consumption modeling

  • Author

    Ciabattoni, Lucio ; Grisostomi, Massimo ; Ippoliti, Gianluca ; Longhi, Sauro

  • Author_Institution
    Dipt. di Ing. dell´Inf., Univ. Politec. delle Marche, Ancona, Italy
  • fYear
    2013
  • fDate
    10-13 Nov. 2013
  • Firstpage
    8022
  • Lastpage
    8027
  • Abstract
    This paper presents a high-resolution model of domestic electricity use, based on Fuzzy Logic Inference System (FIS). The model is built with a “bottom-up” approach and the basic block is the single appliance. Using as inputs patterns of active occupancy (i.e. when people are at home and awake) and typical domestic habits (i.e. start frequency of some appliances), the FIS model give as output the starting probability of each appliance. A post processor enable the appliances start in order to create a one-min resolution electricity demand data. In order to validate the model, electricity demand was recorded over the period of one year within 12 dwellings in the central east coast of Italy. A thorough quantitative comparison is made between the synthetic and measured data sets, showing them to have similar statistical characteristics.
  • Keywords
    domestic appliances; fuzzy logic; fuzzy reasoning; power consumption; power engineering computing; probability; FIS model; Italy central east coast; active occupancy pattern; appliance starting probability; bottom-up approach; domestic electricity use; fuzzy logic inference system; fuzzy logic tool; high-resolution model; household electrical consumption modeling; one-min resolution electricity demand data; post processor; statistical characteristics; typical domestic habits; Adaptation models; Data models; Electricity; Energy management; Fuzzy logic; Home appliances; Load modeling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics Society, IECON 2013 - 39th Annual Conference of the IEEE
  • Conference_Location
    Vienna
  • ISSN
    1553-572X
  • Type

    conf

  • DOI
    10.1109/IECON.2013.6700474
  • Filename
    6700474