• DocumentCode
    3536976
  • Title

    Modeling energy demand aggregators for residential consumers

  • Author

    Di Bella, G. ; Giarre, L. ; Ippolito, Massimo ; Jean-Marie, A. ; Neglia, G. ; Tinnirello, I.

  • Author_Institution
    Dipt. di Energia, Ing. dell´Inf. e Modelli Matematici, Univ. di Palermo, Palermo, Italy
  • fYear
    2013
  • fDate
    10-13 Dec. 2013
  • Firstpage
    6280
  • Lastpage
    6285
  • Abstract
    Energy demand aggregators are new actors in the energy scenario: they gather a group of energy consumers and implement a demand-response paradigm. When the energy provider needs to reduce the current energy demand on the grid, it can pay the energy demand aggregator to reduce the load by turning off some of its consumers loads or postponing their activation. Currently this operation involves only greedy energy consumers like industrial plants. In this paper we want to study the potential of aggregating a large number of small energy consumers like home users as it may happen in smart grids. In particular we want to address the feasibility of such approach by considering which scale the aggregator should reach in order to be able to control a significant power load. The challenge of our study derives from residential users´ demand being much less predictable than that of industrial plants. For this reason we resort to queuing theory to study analytically the problem and quantify the trade-off between load control and tolerable service delays.
  • Keywords
    demand side management; load regulation; queueing theory; smart power grids; demand-response paradigm; energy consumers; energy demand aggregator modeling; greedy energy consumers; home users; industrial plants; power load control; queuing theory; residential consumers; smart grids; Delays; Home appliances; Load modeling; Power demand; Sociology; Statistics; Switches;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control (CDC), 2013 IEEE 52nd Annual Conference on
  • Conference_Location
    Firenze
  • ISSN
    0743-1546
  • Print_ISBN
    978-1-4673-5714-2
  • Type

    conf

  • DOI
    10.1109/CDC.2013.6760882
  • Filename
    6760882