A Real-Time Robust Method for Post-Disaster Load Restoration of Coordinated Power-Transportation System With Vehicle-to-Grid Response
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.
Authors
- Yan Xu (ORCID: https://orcid.org/0000-0002-0503-183X)
- Mingyu Yan (ORCID: https://orcid.org/0000-0001-9040-9480)
- Houbo Xiong (ORCID: https://orcid.org/0000-0003-0179-3818)
- Zhao Yang Dong (ORCID: https://orcid.org/0000-0001-9659-0858)
- Chuangxin Guo (ORCID: https://orcid.org/0000-0003-4472-9525)
- Wei Gan (ORCID: https://orcid.org/0000-0002-6431-1209)
Institutions
- City University of Hong Kong (HK)
- Nanyang Technological University (SG)
- Huazhong University of Science and Technology (CN)
- Zhejiang University (CN)
- Cardiff University (GB)
Publication Details
- Journal
- IEEE Transactions on Smart Grid
- Published
- 2025-05-09
- DOI
- https://doi.org/10.1109/tsg.2025.3568619
- Citations
- 6
- Primary Topic
- Power Systems and Technologies
- Type
- article
- Field-Weighted Citation Impact
- 4.38
Funders
- National Natural Science Foundation of China