• DocumentCode
    3604080
  • Title

    Energy Flow Optimization in Multicarrier Systems

  • Author

    Shabanpour-Haghighi, Amin ; Seifi, Ali Reza

  • Author_Institution
    Dept. of Power & Control, Shiraz Univ., Shiraz, Iran
  • Volume
    11
  • Issue
    5
  • fYear
    2015
  • Firstpage
    1067
  • Lastpage
    1077
  • Abstract
    In this paper, a generalized heuristic approach is proposed to solve the optimal power flow problem in multicarrier energy systems. This technique omits the use of any extra variable, such as dispatch factors or dummy variables required for conventional techniques. The unified proposed approach can be utilized with all evolutionary algorithms. Modeling hub devices with constant efficiency may produce a considerable error in finding the actual optimal operating point of the whole network. However, using variable efficiency model adds complexity to the conventional methods while increasing the computation-demand of these techniques, but this target can be simply implemented by the proposed scheme. A multicarrier energy system consists of an electrical, a natural gas, and a district heating network is analyzed by the proposed algorithm using the modified teaching-learning-based optimization method. Results validate the utilized approach and show that it can successfully reach the global optimal solution of the problem.
  • Keywords
    district heating; evolutionary computation; load flow; natural gas technology; power generation dispatch; computation demand; dispatch factors; district heating network; electrical network; energy flow optimization; evolutionary algorithms; hub devices; multicarrier energy systems; natural gas network; optimal power flow problem; teaching-learning-based optimization method; variable efficiency model; Heat engines; Heat transfer; Natural gas; Optimization; Pipelines; Resistance heating; Water heating; Energy hub; heuristic algorithms; multi-carrier energy system; multicarrier energy system; optimal power flow; optimization problem;
  • fLanguage
    English
  • Journal_Title
    Industrial Informatics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1551-3203
  • Type

    jour

  • DOI
    10.1109/TII.2015.2462316
  • Filename
    7172514