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Dynamic Restoration Electricity Price Optimization Method to Enhance the Resilience of Distribution Networks with MMG
  • +2
  • Hongkun Wang,
  • yu jie Gao,
  • Hong Zhang,
  • Dong Mei Yan,
  • Hongwei Li
Hongkun Wang
Shihezi University
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yu jie Gao
Shihezi University
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Hong Zhang
Shihezi University

Corresponding Author:[email protected]

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Dong Mei Yan
Shihezi University
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Hongwei Li
Shihezi University
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Abstract

Resilience is one of the main features of smart distribution network, and a microgrid access to the distribution network provides an effective way to improve resilience. Microgrid and distribution network belong to different interests, so it is necessary to use price leverage to actively guide microgrids and flexible resources within microgrid to participate in post-disaster restoration of distribution network and enhance the resilience. Firstly, this paper proposes a dynamic restoration electricity price response mechanism for distribution network after extreme disasters and constructs a power response model for loads and electric vehicles within the microgrid. Secondly, the optimal scheduling model of distribution network with multiple-microgrid is proposed to improve the restoration rate of critical loads(RRCL) in the distribution network. Single microgrid achieves the largest microgrid revenue and restoration contribution, and multi-microgrid uses the power headroom index to optimize the dynamic restoration electricity price to achieve the smallest power purchase cost of distribution network. Finally, the optimal scheduling method for resilience enhancement of distribution networks with MMG considering dynamic restoration electricity price response mechanism is validated by dual microgrid access to IEEE 33-node distribution system. The simulation results show that the proposed optimization method effectively improves the RRCL of distribution network.
16 Oct 2023Assigned to Editor
16 Oct 2023Submission Checks Completed
18 Oct 2023Review(s) Completed, Editorial Evaluation Pending
16 Nov 2023Reviewer(s) Assigned