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Coordinated DG-Tie planning in distribution networks based on temporal scenarios

Author

Listed:
  • Xiang, Yue
  • Zhou, Lili
  • Su, Yunche
  • Liu, Jichun
  • Huang, Yuan
  • Liu, Junyong
  • Lei, Xia
  • Sun, Zhang
  • Xu, Weiting
  • Zhang, Wentao

Abstract

Optimal planning of distributed generation (DG) in distribution networks is key for improving energy utilization efficiency and system operation benefits. Considering the uncertainties and temporal correlations of DG output and load demand, a multi-scenario chance-constrained economic model for DG planning is established in this paper. The model considers the comprehensive benefits of environmental, reliability and other aspects, as well as the active curtailment management of DGs. Thereafter, the model is extended to the coordinated planning of both DGs and tie lines, which is formulated as a multi-objective model. An improved genetic algorithm based solving strategy integrated with game multi-objective decision method is proposed. The feasibility and effectiveness of the proposed models are verified on the IEEE 33-bus distribution system. The impacts of natural resource distribution, confidence level, unit environmental cost and other parameters are investigated as well. The case studies also prove the integration of complementary DG generation could help improve the maximum capacity of DG and indicate the environmental benefit is the vital incentive to introduce DG into the distribution network.

Suggested Citation

  • Xiang, Yue & Zhou, Lili & Su, Yunche & Liu, Jichun & Huang, Yuan & Liu, Junyong & Lei, Xia & Sun, Zhang & Xu, Weiting & Zhang, Wentao, 2018. "Coordinated DG-Tie planning in distribution networks based on temporal scenarios," Energy, Elsevier, vol. 159(C), pages 774-785.
    • Handle: RePEc:eee:energy:v:159:y:2018:i:c:p:774-785
    DOI: 10.1016/j.energy.2018.06.159
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    References listed on IDEAS

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    1. Tanwar, Surender Singh & Khatod, D.K., 2017. "Techno-economic and environmental approach for optimal placement and sizing of renewable DGs in distribution system," Energy, Elsevier, vol. 127(C), pages 52-67.
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    Cited by:

    1. Xiang, Yue & Dai, Jiakun & Xue, Ping & Liu, Junyong, 2023. "Autonomous topology planning for distribution network expansion: A learning-based decoupled optimization method," Applied Energy, Elsevier, vol. 348(C).
    2. Xiang, Yue & Zhou, Lili & Huang, Yuan & Zhang, Xin & Liu, Youbo & Liu, Junyong, 2021. "Reactive coordinated optimal operation of distributed wind generation," Energy, Elsevier, vol. 218(C).

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