Resilience-Oriented Coordinated Topology Reconfiguration of Electricity and Drainage Networks With Distributed Mobile Emergency Resources

Yingping Cao, Bin Zhou, Chi Yung Chung, Ke Zhou, Lipeng Zhu, Zhikang Shuai

Research output: Journal article publicationJournal articleAcademic researchpeer-review

23 Citations (Scopus)

Abstract

This paper proposes a coordinated topology reconfiguration method for power distribution networks (PDNs) and urban drainage networks (UDNs) to facilitate the load restoration and flood prevention with diversified mobile emergency resources (MERs) under rainstorm disasters. The proposed method synergistically controls the pumps-sluice clusters and drainage rescue vehicles (DRVs) to reconfigure the optimal draining route and flow direction of UDNs for resilience enhancement of PDNs with localized damages. Mobile emergency generators (MEGs) and renewable distributed generations (DGs) are optimally dispatched for supporting PDN reconfiguration to guarantee a reliable electricity supply for UDN drainage facilities under rainstorm-induced transportation interruptions and power outages. Then, a multi-network coupling model with hydrodynamic partial differential equations (PDEs) of pressure and free-surface flows is developed to describe the failure propagation across PDNs, UDNs and urban transportation networks (UTNs). Furthermore, an equivalent transfer matrix of dynamic UDN flows is derived based on Laplace transforms to cope with the PDE-constrained optimization problem for computational burden alleviation. Comparative results have illustrated the superior performance of the proposed method in reducing the critical load curtailment of PDNs and inundation depth of UTN roads.

Original languageEnglish
Pages (from-to)786-800
Number of pages15
JournalIEEE Transactions on Smart Grid
Volume16
Issue number1
DOIs
Publication statusPublished - Jan 2025

Keywords

  • coordinated reconfiguration
  • distribution network
  • Drainage network
  • mobile emergency resources
  • rainstorms

ASJC Scopus subject areas

  • General Computer Science

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