Hybrid Spatio-Temporal scale decentralized restoration strategy for interdependent electricity and gas systems to enhance restoration efficiency and security
• The restoration processes in electricity and gas systems are coordinated in both spatial and temporal scales to enhance restoration efficiency and security. • The electricity and gas system coordination are achieved in a decentralized manner to preserve their information privacy. • A high-accuracy gas flow dynamics model is proposed. • An efficient solution algorithm is proposed with great calculation performance. The ever-increasing couplings between electricity and gas systems highlight the coordinated restoration decisions for interdependent electricity and gas system (IEGS) to enhance resilience. However, the distinct timescales of power and gas flow rates as well as information privacy concern cause additional complexities in making restoration decisions, and large calculation scale and nonconvexity also results in computational obstacles. To address these issues, this paper proposes a hybrid spatio-temporal scale decentralized restoration strategy for IEGS to enhance restoration efficiency and security. First, in the spatial scale, the network sectionalizing and the restoration processes in sectionalized electricity and gas systems are coordinated in a decentralized manner with limited boundary information interactions to respect information privacy. Next, the impacts of distinct timescales of power and gas flow rates are explored to accelerate restoration, and a linear gas flow dynamics model is also proposed to capture the gas transmission dynamics with high accuracy, enhancing restoration security. Furthermore, a decomposition-based alternating direction method of multipliers algorithm is proposed to efficiently solve the proposed IEGS restoration strategy, showing good calculation time and convergence performance. Finally, the effectiveness of the proposed restoration strategy is validated in a T118N20 test system and a real-world system, demonstrating the enhanced restoration efficiency, security alongside commendable computational performance.
Authors
- Zhenzhi Lin (ORCID: https://orcid.org/0000-0003-2125-9604)
- Kunjie Liang (ORCID: https://orcid.org/0000-0002-2586-5989)
- Hongtao Wang (ORCID: https://orcid.org/0000-0002-5522-455X)
Institutions
- Shandong University (CN)
- Zhejiang University (CN)
Publication Details
- Journal
- International Journal of Electrical Power & Energy Systems
- Published
- 2024-09-05
- DOI
- https://doi.org/10.1016/j.ijepes.2024.110214
- Primary Topic
- Integrated Energy Systems Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China