• DocumentCode
    665270
  • Title

    Smart heating system control strategy to enhance comfort and increase renewable energy penetration

  • Author

    Hakimi, S.M. ; Moghaddas-Tafreshi, S.M. ; Alamuti, Mohsen Mohammadi

  • Author_Institution
    Fac. of Electr. Eng., K.N. Toosi Univ. of Technol., Tehran, Iran
  • fYear
    2013
  • fDate
    14-14 Nov. 2013
  • Firstpage
    191
  • Lastpage
    196
  • Abstract
    Heating systems have played an important role in building energy and comfort management. This paper set forth a novel intelligent residential heating system controller that has smart grid functionality. In the smart grid, demand response systems now have the ability to not only engage commercial and industrial customers, but also the individual residential customers. Additionally, the ability exists to have automated control systems which operate on an availability of renewable energy and welfare of customers. In this paper one possible implementation of an active controller will be examined. An active controller operates by responding to a combination of internal set points and external signals from local control entity. The optimization objective of the heating systems management is to minimize the cost of smart microgrid, minimize the size of smart microgrid units, minimize energy import from distribution grid and maximize reliability of the smart microgrid. This means that, smart heating system and renewable energy can work well together and their individual benefits can be added together when used in combination. Simulation studies are used to demonstrate the capability on the proposed heating system controller on the planning of a smart microgrid system.
  • Keywords
    distributed power generation; intelligent control; smart power grids; space heating; active controller; automated control systems; demand response systems; distribution grid; heating systems management; intelligent residential heating system controller; renewable energy penetration; smart heating system control strategy; smart microgrid; Computational modeling; Data models; Gaussian processes; Predictive models; Standards; Training; Wind power generation; Active controller; heating system; renewable energy; smart microgrid;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Energy Systems (IWIES), 2013 IEEE International Workshop on
  • Conference_Location
    Vienna
  • Type

    conf

  • DOI
    10.1109/IWIES.2013.6698584
  • Filename
    6698584