Abstract
With the proliferation of electric vehicles (EVs), vehicle-to-grid (V2G) capability emerges as a potential resource for load restoration after a large disruption. This paper presents a real-time post-disaster load restoration method for the coordinated power distribution networks (PDN) and urban traffic networks (UTN) with V2G response. The multi-period restoration problem is modeled as a dynamic programming-based multi-stage robust optimization model, addressing uncertainties of renewable generation and traffic demands. It incorporates a dynamic traffic assignment scheme to characterize vehicle travels and V2G services within short time slots. Then, an improved robust dual dynamic programming algorithm is proposed to solve the multi-stage robust optimization problem. For online application, the solved value functions from each stage serve as per-period policies, leveraging knowledge of future uncertainties to quickly guide real-time load restoration through distributed resource dispatch, network reconfiguration, and V2G assignments. Numerical experiments with a 33-bus PDN and 20-road UTN, plus a real-world 91-bus PDN with 35-road UTN, validate the effectiveness of proposed restoration method. © 2025 IEEE.
| Original language | English |
|---|---|
| Pages (from-to) | 3195-3209 |
| Journal | IEEE Transactions on Smart Grid |
| Volume | 16 |
| Issue number | 4 |
| Online published | 9 May 2025 |
| DOIs | |
| Publication status | Published - Jul 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
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SDG 11 Sustainable Cities and Communities
Research Keywords
- dynamic traffic flow
- multi-stage optimization
- post-disaster real-time restoration
- power-transportation system
- uncertainties
- Vehicle-to-grid
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