• DocumentCode
    17026
  • Title

    Optimization of Distribution Network Incorporating Distributed Generators: An Integrated Approach

  • Author

    Sicong Tan ; Jian-Xin Xu ; Panda, S.K.

  • Author_Institution
    NUS Grad. Sch. for Integrative Sci. & Eng. (NGS), Nat. Univ. of Singapore, Singapore, Singapore
  • Volume
    28
  • Issue
    3
  • fYear
    2013
  • fDate
    Aug. 2013
  • Firstpage
    2421
  • Lastpage
    2432
  • Abstract
    Previous studies of distributed power and network focused only on the optimization of either the microgrid load dispatch or reconfiguration power loss. Micorgrid economic load dispatch approach normally does not support distribution network. Network reconfiguration usually does not take distributed generators into consideration. Thus, it is necessary to integrate these two sub-problems together in order to benefit the whole network. In this paper, an integrated solution that takes care of both microgrid load dispatch and network reconfiguration is proposed. The stochastic nature of wind, PV and load is taken into consideration. The forecasting of the wind, PV and load data are considered. The four bio-inspired optimization schemes are adopted to solve the problem. The results obtained have shown that the four optimization techniques are all capable of solving this problem. By using the integrated approach, microgrid can be incorporated into the network more effectively. The network can adjust itself more efficiently to allow utilization of the renewable energy resources.
  • Keywords
    distributed power generation; distribution networks; load forecasting; optimisation; photovoltaic power systems; power generation dispatch; power generation economics; wind power plants; PV stochastic nature; bio-inspired optimization scheme; distributed generators; distributed power; distribution network optimization; integrated approach; load stochastic nature; micorgrid economic load dispatch approach; microgrid load dispatch optimization; network reconfiguration; reconfiguration power loss; renewable energy resources; wind stochastic nature; wind-PV-load data forecasting; Power distribution planning; power generation economics; reconfiguration; renewable energy;
  • fLanguage
    English
  • Journal_Title
    Power Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8950
  • Type

    jour

  • DOI
    10.1109/TPWRS.2013.2253564
  • Filename
    6497085