Decentralized robust unit commitment for AC/DC interconnected power systems considering wind power uncertainty
•A decentralized robust optimization framework for bulk AC/DC interconnected systems is proposed.•Unit commitment and reserve allocation are coordinated to achieve the optimal operation.•Multiple flexible resources are involved to enhance the robustness and flexibility.•The hierarchical control arch...
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Veröffentlicht in: | International journal of electrical power & energy systems 2022-10, Vol.141, p.108203, Article 108203 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | •A decentralized robust optimization framework for bulk AC/DC interconnected systems is proposed.•Unit commitment and reserve allocation are coordinated to achieve the optimal operation.•Multiple flexible resources are involved to enhance the robustness and flexibility.•The hierarchical control architecture is developed to coordinate the AC/DC interconnected systems in a decentralized manner.•An integrated algorithm of ATC and C&CG is adopted to solve the proposed problem.
The growing penetration of wind energy and the increasing AC/DC interconnections of regional power grids critically need to coordinate the multi-area unit commitment and reserve schedules. This paper proposes a decentralized robust optimization framework for the unit commitment and reserve allocation into bulk AC/DC interconnected systems. In the proposed framework, the scheduling problem is decomposed and handled by the analytical target cascading (ATC) technique. The upper-level master problem coordinates and updates the transmission plan of the high-voltage direct current (HVDC) tie-line. The lower-level regional sub-problems are formulated as robust security-constrained unit commitment models to co-optimize the generation and flexible reserve scheme in a parallel manner. The regional sub-problems precisely model the time-coupled flexible reserve supply of multiple flexible resources to cope with the wind power uncertainty and are solved by the column-and-constraint generation algorithm. Numerical simulations are conducted and comparative analysis is performed to validate the effectiveness and feasibility of the proposed framework. |
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ISSN: | 0142-0615 1879-3517 |
DOI: | 10.1016/j.ijepes.2022.108203 |