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Nikoobakht, A., Aghaei, J., Afrasiabi, M. and Vahidinasab, V. 
ORCID: 0000-0002-0779-8727,
2022.
Collaborative resilience to extreme weather in decentralized co-operation of electricity and natural gas distribution systems.
Electric Power Systems Research, 212: 108658.
ISSN 0378-7796
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Abstract
The flexibility of the power-to-gas (P2G) technologies and natural gas units (NGUs) can enhance the resilience of the electric distribution system (EDS) considering the high penetration of renewable energy resources (RERs). The decentralized collaborative operation (co-operation) of electric distribution systems and natural gas systems (EDSs&NGSs) considering information privacy preserving can enhance the resilience during an extreme hurricane. To address this issue, this paper proposes a three-level hierarchal solution to decompose the centralized co-operation of the EDS&NGS framework in which an independent decision-making strategy and information privacy preserving for both network operators are simultaneously addressed. Furthermore, in this paper, a min–max robust resilience-constrained co-optimization model is presented to enhance the resilience of the integrated EDS&NGS against worst-case N-k contingencies and wind power generation uncertainty under extreme hurricane events. To attain the spatial dynamics of extreme hurricanes, a the multi-zone and multi-time extreme hurricanes model is considered. Then, a column-and-constraints generation (C&CG) algorithm is used to solve the proposed robust resilience-constrained co-optimization model. To verify the effectiveness of the model, we conducted experiments on a modified IEEE-33-bus-10-node/123-bus-20-node EDS&NGS. The numerical results show that the proposed robust resilience-constrained co-operation of EDS&NGS problem is an effective model for enhancing EDS resilience.
| Item Type: | Journal article | ||||||||
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| Publication Title: | Electric Power Systems Research | ||||||||
| Creators: | Nikoobakht, A., Aghaei, J., Afrasiabi, M. and Vahidinasab, V. | ||||||||
| Publisher: | Elsevier BV | ||||||||
| Date: | November 2022 | ||||||||
| Volume: | 212 | ||||||||
| ISSN: | 0378-7796 | ||||||||
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| Divisions: | Schools > School of Science and Technology | ||||||||
| Record created by: | Linda Sullivan | ||||||||
| Date Added: | 04 Aug 2022 07:41 | ||||||||
| Last Modified: | 02 Aug 2023 03:00 | ||||||||
| URI: | https://irep.ntu.ac.uk/id/eprint/46823 |
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