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Interval optimization based coordination scheduling of gas-electricity coupled system considering wind power uncertainty, dynamic process of natural gas flow and demand response ma...
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| Veröffentlicht in: | Energy reports 6(2020) vom: Nov., Seite 216-227 |
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| Personen und Körperschaften: | , , , , , |
| Titel: | Interval optimization based coordination scheduling of gas-electricity coupled system considering wind power uncertainty, dynamic process of natural gas flow and demand response management/ Yachao Zhang, Zhanghao Huang, Feng Zheng, Rongyu Zhou, Xueli An, Yinghai Li |
| Format: | E-Book-Kapitel |
| Sprache: | Englisch |
| veröffentlicht: |
2020
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| Gesamtaufnahme: |
: Energy reports, 6(2020) vom: Nov., Seite 216-227
, volume:6 |
| Schlagwörter: | |
| Quelle: | Verbunddaten SWB Lizenzfreie Online-Ressourcen |
| Zusammenfassung: | With the remarkable growth of natural gas consumption and the development of renewable energy worldwide in recent years, the penetration capacity of gas-fired generators and uncertain renewable energy has significantly become larger, which poses a great challenge to the reliable and economic operation of the gas-electricity interconnected system. This paper proposes an interval optimization based coordination scheduling model for the gas-electricity coupled system considering the dynamic characteristics of natural gas flow, wind power integration and demand response management. By introducing the arithmetic and order relation of interval numbers, the objective function and corresponding constraints for the interval-based dispatch model can be converted into the deterministic expressions with degrees of pessimism, then the proposed model can be solved in the master-subproblem framework. On this basis, two case studies are implemented on the 6-bus power system integrated with 6-node natural gas system and the modified IEEE 118-bus system with 10-node natural gas system to investigate the impact of gas flow dynamic process, demand response management, wind power uncertainty on the scheduling solution of the coupled systems. Moreover, the scenario-based stochastic optimization and robust optimization methods are carried out for comparison. Simulation results demonstrate the effectiveness of the proposed interval optimization method. |
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| ISSN: |
2352-4847
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| DOI: | 10.1016/j.egyr.2019.12.013 |
| Zugang: | Open Access |