• DocumentCode
    2626022
  • Title

    Application of ANN and DSM techniques for peak load management a case study

  • Author

    Ravi Babu, P. ; Divya, V. P Sree ; Venkatesh, K. ; Kodad, S.F. ; Ram, B. V Sankar

  • Author_Institution
    EEE Dept., CVR Coll. of Eng., Hyderabad
  • fYear
    2008
  • fDate
    21-25 July 2008
  • Firstpage
    169
  • Lastpage
    174
  • Abstract
    The resources for electrical energy are depleting and hence the gap between the supply and the demand is continuously increasing. Under such circumstances, the option left is optimal utilization of available energy resources. To overcome this problem recently, a concept of demand side management (DSM) has emerged in power system planning and management. The main idea of DSM is to discuss the mutual benefits between supplier and consumer for maximum benefits and minimum inconvenience. The work presented in this paper gives the results of application of neural network and DSM techniques applied to an industrial consumer. The study indicates the improvement in energy efficiency of the system in terms of load factor, in addition the consumer also gets saving or reduction in the energy bill due to lowering of maximum demand (MD).
  • Keywords
    demand side management; neural nets; power engineering computing; power system management; power system planning; demand side management; electrical energy; energy efficiency improvement; energy resources; maximum demand; neural network; peak load management; power system management; power system planning; Elasticity; Electricity supply industry; Energy management; IEEE members; Load management; Load modeling; Power engineering and energy; Power system management; Power system modeling; Shape; DSM: Demand Side Management; DT: Differential Tariff; EUEC: End Use Equipment Control; LPT: Load Priority Technique; MD: Maximum Demand;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Technologies in Electrical and Electronics Engineering, 2008. SIBIRCON 2008. IEEE Region 8 International Conference on
  • Conference_Location
    Novosibirsk
  • Print_ISBN
    978-1-4244-2133-6
  • Electronic_ISBN
    978-1-4244-2134-3
  • Type

    conf

  • DOI
    10.1109/SIBIRCON.2008.4602568
  • Filename
    4602568