• DocumentCode
    2402987
  • Title

    Optimal location of TCSC and SVC for enhancement of ATC in a de-regulated environment using RGA

  • Author

    MadhusudhanaRao, G. ; Ramarao, P. Vijaya ; Kumar, T. Jayanth

  • Author_Institution
    Dept. Of EEE, K L Univ., Guntur, India
  • fYear
    2010
  • fDate
    28-29 Dec. 2010
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In this paper the use of TCSC and SVC to maximize Available Transfer Capability (ATC) generally defined as the maximum power transfer transaction between a specific power-seller and a power-buyer in a network during normal and contingency cases. In this paper, ATC is computed using Continuous Power Flow (CPF) method considering both line thermal limit as well as bus voltage limits. Real-code Genetic Algorithm is used as the optimization tool to determine the location as well as the controlling parameter of TCSC or SVC simultaneously. The performance of the Real-code Genetic Algorithm has been tested on IEEE 24-Bus Reliability Test System. Improving of ATC is an important issue in the current de-regulated environment of power systems. The Available Transfer Capability (ATC) of a transmission network is the unutilized transfer capabilities of a transmission network for the transfer of power for further commercial activity, over and above already committed usage. Power transactions between a specific seller bus/area and a buyer bus/area can be committed only when sufficient ATC is available. ATC can be limited usually by heavily loaded circuits and buses with relatively low voltages. It is well known that FACTS technology can control voltage magnitude, phase angle and circuit reactance. Using these devices may redistribute the load flow, regulating bus voltages. Therefore, it is worthwhile to investigate the impact of FACTS controllers on the ATC.
  • Keywords
    flexible AC transmission systems; genetic algorithms; load flow; maximum power point trackers; transmission networks; ATC; FACTS controllers; RGA; SVC; TCSC; available transfer capability; continuous power flow method; maximum power transfer; optimal location; real-code genetic algorithm; transmission network; Biological cells; Load flow; Power capacitors; Shunt (electrical); Static VAr compensators; Thyristors; ATC; Load flows; Real-code Genetic Algorithm; SVC; TCSC; power seller/buyer;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Computing Research (ICCIC), 2010 IEEE International Conference on
  • Conference_Location
    Coimbatore
  • Print_ISBN
    978-1-4244-5965-0
  • Electronic_ISBN
    978-1-4244-5967-4
  • Type

    conf

  • DOI
    10.1109/ICCIC.2010.5705874
  • Filename
    5705874