• DocumentCode
    2717576
  • Title

    Optimal UPFC based on Genetics Algorithm to improve the steady-state performance of HELENSÄHKÖVERKKO OY 110 KV NETWORK at increasing the loading pattern

  • Author

    Othman, Ahmed M. ; Lehtonen, Matti ; El-Arini, Mahdi M.

  • Author_Institution
    Electr. Power Dept., Helsinki Univ. of Technol., Espoo, Finland
  • fYear
    2010
  • fDate
    16-19 May 2010
  • Firstpage
    162
  • Lastpage
    166
  • Abstract
    Flexible Alternating Current Transmission Systems (FACTS) devices represent very high efficient tools for controlling the operations and enhancing the performances of the electrical power network. Unified Power Flow Controller (UPFC) is considered as the most powerful member of the FACTS family, where it has both shunt and series controller inside its frame. This option gives to UPFC the power to control the voltage profile and the transmission lines flow simultaneously. In this paper, we use the Genetics Algorithm (GA) to find the optimal location and the optimal settings of UPFC to improve the performance of the power system specially solving the transmission lines overloading during normal operation and configuration at increasing the loading conditions. This procedure is proposed to be applied on Helsinki HELENSÄHKÖVERKKO OY 110 KV NETWORK until the operating conditions of Year 2020. To show the validity of the technique, it will be tested on the IEEE 6-bus system.
  • Keywords
    Control systems; Genetic algorithms; Load flow; Optimal control; Power system interconnection; Power systems; Power transmission lines; Static VAr compensators; Steady-state; Voltage control; Genetic Algorithm (GA); Increasing loading pattern; Loadability; Optimal location; Optimal setting; Unified Power Flow controller (UPFC);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Environment and Electrical Engineering (EEEIC), 2010 9th International Conference on
  • Conference_Location
    Prague, Czech Republic
  • Print_ISBN
    978-1-4244-5370-2
  • Electronic_ISBN
    978-1-4244-5371-9
  • Type

    conf

  • DOI
    10.1109/EEEIC.2010.5489990
  • Filename
    5489990