• DocumentCode
    423366
  • Title

    Market-based planning of transmission network using genetic algorithm

  • Author

    Xu, Z. ; Dong, Z.Y.

  • Author_Institution
    Sch. of Inf. Technol. & Electr. Eng., Queensland Univ., St. Lucia, Qld., Australia
  • fYear
    2004
  • fDate
    16-16 Sept. 2004
  • Firstpage
    826
  • Lastpage
    831
  • Abstract
    The reconstruction and deregulation have brought fundamental changes to many aspects of power system operation and management. As a result, the planning activity is no longer dominated by the system operator. The deregulation has also brought many uncertainties and constraints to the system planning area. Therefore, the traditional centralized expansion planning approach will face difficulties in a market environment and new planning approaches are needed. In this paper, a market-oriented planning objective for transmission network expansion has been developed, which aims at maximizing the overall benefit from network expansion while considering critical constraints, such as power flow balance and transmission capacities. The planning objective has been solved by a genetic algorithm (GA) to achieve the best available expansion plan. The IEEE 14-bus system is used to test the developed method.
  • Keywords
    genetic algorithms; load flow; power markets; power transmission planning; GA; IEEE 14-bus system; critical constraint; genetic algorithm; market deregulation; market reconstruction; market-based planning; power flow balance; power system management; power system operation; transmission capacity; transmission network; Electricity supply industry; Electricity supply industry deregulation; Energy consumption; Energy management; Genetic algorithms; Investments; Load flow; Power system management; Power system planning; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Probabilistic Methods Applied to Power Systems, 2004 International Conference on
  • Conference_Location
    Ames, IA
  • Print_ISBN
    0-9761319-1-9
  • Type

    conf

  • Filename
    1378794