• DocumentCode
    3729802
  • Title

    Real-time battery management algorithm for peak demand shaving in small energy communities

  • Author

    Seksak Pholboon;Mark Sumner;Edward Christopher;Stuart A. Norman

  • Author_Institution
    Department of Electrical and Electronic Engineering, University of Nottingham, UK
  • fYear
    2015
  • Firstpage
    19
  • Lastpage
    24
  • Abstract
    One of the solutions to tackle the problems of high peak demand and grid instability due to high photovoltaic (PV) power penetration is to deploy a battery storage system. This paper presents a real-time battery management algorithm (BMA) for peak demand shaving in small energy communities with grid-connected PV systems. The BMA aims to control the charge/discharge of the community battery storage using measurement of the instantaneous power consumption of the community. Historical data records of community daily energy consumption and available renewable energy are taken into account to manage the charge/discharge of the battery. Simulation results show the effectiveness of the BMA which is able to reduce the peak energy consumption by 35%, increase PV self-consumption by 47% and reduce transmission line losses during the peak period by 56% when compared to a PV system without the battery storage.
  • Keywords
    "Batteries","Discharges (electric)","Renewable energy sources","Data models","Biological system modeling","Resistance","Power generation"
  • Publisher
    ieee
  • Conference_Titel
    Innovative Smart Grid Technologies Latin America (ISGT LATAM), 2015 IEEE PES
  • Type

    conf

  • DOI
    10.1109/ISGT-LA.2015.7381123
  • Filename
    7381123