• DocumentCode
    3134109
  • Title

    Transmission network expansion planning considering unit commitment problem simultaneously

  • Author

    Golestani, S. ; Tadayon, M. ; Pirbazari, A. Mehdipour

  • Author_Institution
    Energy Ind. Eng. & Design (EIED), Tehran, Iran
  • fYear
    2010
  • fDate
    11-13 Oct. 2010
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Transmission Network Expansion Planning (TNEP) is an important part of power system planning in new structured power market. Its goal is to minimize the network construction and operational cost while satisfying the demand increase, considering technical and economic conditions. Since change in Unit Commitment (UC), influences transmission lines, this paper presents an Integer Coded Genetic Algorithm (ICGA) to solve both problems together. Genetic algorithm can consider all generation and network constraints. Also random behavior of genetic algorithm can simulate real probabilities such as uncertainty in generation. Considering uncertainty for some units, in each iteration, it can find out the probability of congestion for each line. After all iterations it can highlight the transmission lines which need expansion, because of high congestion probability. Simulation results of the proposed idea are presented for IEEE30-bus network.
  • Keywords
    genetic algorithms; power markets; power transmission economics; power transmission planning; ICGA; TNEP; integer coded genetic algorithm; network construction minimization; operational cost minimization; power market; power transmission network expansion planning; transmission lines; unit commitment problem; Biological cells; Biological system modeling; Power system reliability; Power transmission lines; Schedules; integer coded genetic algorithm; transmission network expansion planning; unit commitment;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Innovative Smart Grid Technologies Conference Europe (ISGT Europe), 2010 IEEE PES
  • Conference_Location
    Gothenburg
  • Print_ISBN
    978-1-4244-8508-6
  • Electronic_ISBN
    978-1-4244-8509-3
  • Type

    conf

  • DOI
    10.1109/ISGTEUROPE.2010.5638905
  • Filename
    5638905