• DocumentCode
    791645
  • Title

    Efficient linear programming algorithm for the transmission network expansion planning problem

  • Author

    Hashimoto, S.H.M. ; Romero, R. ; Mantovani, J.R.S.

  • Author_Institution
    Electr. Eng. Dept., Sao Paulo State Univ., Brazil
  • Volume
    150
  • Issue
    5
  • fYear
    2003
  • Firstpage
    536
  • Lastpage
    542
  • Abstract
    The transmission network planning problem is a nonlinear integer mixed programming problem (NLIMP). Most of the algorithms used to solve this problem use a linear programming subroutine (LP) to solve LP problems resulting from planning algorithms. Sometimes the resolution of these LPs represents a major computational effort. The particularity of these LPs in the optimal solution is that only some inequality constraints are binding. This task transforms the LP into an equivalent problem with only one equality constraint (the power flow equation) and many inequality constraints, and uses a dual simplex algorithm and a relaxation strategy to solve the LPs. The optimisation process is started with only one equality constraint and, in each step, the most unfeasible constraint is added. The logic used is similar to a proposal for electric systems operation planning. The results show a higher performance of the algorithm when compared to primal simplex methods.
  • Keywords
    linear programming; load flow; power transmission planning; relaxation; dual simplex algorithm; electric systems operation planning; equality constraint; inequality constraints; linear programming algorithm; linear programming subroutine; nonlinear integer mixed programming problem; optimisation process; planning algorithms; power flow equation; primal simplex methods; relaxation strategy; transmission network expansion planning;
  • fLanguage
    English
  • Journal_Title
    Generation, Transmission and Distribution, IEE Proceedings-
  • Publisher
    iet
  • ISSN
    1350-2360
  • Type

    jour

  • DOI
    10.1049/ip-gtd:20030656
  • Filename
    1233535