• DocumentCode
    1631161
  • Title

    An approach of DSM techniques for domestic load management using fuzzy logic

  • Author

    Ravibabu, P. ; Praveen, A. ; Chandra, C.V. ; Reddy, Pappagari Raghavendra ; Teja, M.

  • Author_Institution
    EEE Dept., CVR Coll. of Eng., Hyderabad, India
  • fYear
    2009
  • Firstpage
    1303
  • Lastpage
    1307
  • Abstract
    Electrical energy is a vital feature for any developing nation. To meet the growing demand, power generating plants of all types are being installed; even then the gap between the supply and demand is continuously increasing due to the depletion of natural resources. Hence, the way to over come the problem is optimal utilization of available energy sources. In this paper, a methodology is shown to solve to design a model for load management during peak hours in case of domestic loads in both peak hours and off peak hours aiming to reduce the gap between the demand and the supply of electrical energy. Such that consumers and supplier both get beneficial at the same time. The paper also presents the application of fuzzy logic and DSM techniques to the domestic loads, where in the power consumption can be limited during the peak hours there by achieving power conservation. The current method developed is the extension and the part of the demand side management. Simulation results are presented to show effectiveness of the proposed fuzzy logic and demand side management strategy for load management.
  • Keywords
    control system synthesis; demand side management; energy conservation; fuzzy control; power consumption; DSM technique; controller design; demand side management; domestic load management; electrical energy; fuzzy logic; off peak hour; power conservation; power consumption; Educational institutions; Energy conservation; Energy consumption; Fuzzy logic; Government; Load flow control; Load management; Load modeling; Power engineering and energy; Power system simulation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems, 2009. FUZZ-IEEE 2009. IEEE International Conference on
  • Conference_Location
    Jeju Island
  • ISSN
    1098-7584
  • Print_ISBN
    978-1-4244-3596-8
  • Electronic_ISBN
    1098-7584
  • Type

    conf

  • DOI
    10.1109/FUZZY.2009.5277401
  • Filename
    5277401