• DocumentCode
    662406
  • Title

    Control methodologies: Peak reduction algorithms for DNO owned storage devices on the Low Voltage network

  • Author

    Rowe, Matthew ; Holderbaum, William ; Potter, Ben

  • Author_Institution
    Sch. of Syst. Eng., Univ. of Reading, Reading, UK
  • fYear
    2013
  • fDate
    6-9 Oct. 2013
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    The Distribution Network Operators (DNOs) role is becoming more difficult as electric vehicles and electric heating penetrate the network, increasing the demand. As a result it becomes harder for the distribution networks infrastructure to remain within its operating constraints. Energy storage is a potential alternative to conventional network reinforcement such as upgrading cables and transformers. The research presented here in this paper shows that due to the volatile nature of the LV network, the control approach used for energy storage has a significant impact on performance. This paper presents and compares control methodologies for energy storage where the objective is to get the greatest possible peak demand reduction across the day from a pre-specified storage device. The results presented show the benefits and detriments of specific types of control on a storage device connected to a single phase of an LV network, using aggregated demand profiles based on real smart meter data from individual homes. The research demonstrates an important relationship between how predictable an aggregation is and the best control methodology required to achieve the objective.
  • Keywords
    demand side management; distribution networks; electric heating; electric vehicles; smart meters; DNO owned storage device; LV network; distribution network operator; electric heating; electric vehicle; low voltage network; network reinforcement; peak reduction algorithm; prespecified energy storage storage device; real smart meter data; Discharges (electric); Energy storage; Low voltage; Performance evaluation; Prediction algorithms; Real-time systems; Smart grids; Control systems; Energy storage; Optimization; Power demand; Power system control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Innovative Smart Grid Technologies Europe (ISGT EUROPE), 2013 4th IEEE/PES
  • Conference_Location
    Lyngby
  • Type

    conf

  • DOI
    10.1109/ISGTEurope.2013.6695291
  • Filename
    6695291