IET Generation, Transmission & Distribution (Jun 2024)

Dynamic restoration electricity price optimization method to enhance the resilience of distribution networks with multiple‐microgrids

  • Hongkun Wang,
  • Yujie Gao,
  • Hong Zhang,
  • Dongmei Yan,
  • Hongwei Li

DOI
https://doi.org/10.1049/gtd2.13199
Journal volume & issue
Vol. 18, no. 12
pp. 2230 – 2241

Abstract

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Abstract Resilience is one of the main features of smart distribution networks, and a microgrid (MG) access to the distribution network provides an effective way to improve resilience. MG and distribution network belong to different interests, so it is necessary that MGs and flexible resources are actively guided through price leverage. In this way, MGs take part in the post‐disaster restoration and enhance its resilience. Firstly, this paper proposes a dynamic restoration electricity price response mechanism after extreme disasters and constructs a power response model for loads and electric vehicles within the MGs. Secondly, the optimal scheduling model of the distribution network with multiple‐microgrids (MMG) is proposed to improve the restoration rate of critical loads (RRCL). Single microgrid achieves the largest microgrid revenue and restoration contribution, and MMG 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 an IEEE 33‐node distribution system. The simulation results show that the proposed optimization method effectively improves the RRCL of distribution network.

Keywords