Robust Distribution Network Reconfiguration Using Mapping-based Column-and-Constraint Generation
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arXiv
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| Hauptverfasser: | , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866912404257898496 |
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| author | Zhang, Runjie Qu, Kaiping Zhao, Changhong Huang, Wanjun |
| author_facet | Zhang, Runjie Qu, Kaiping Zhao, Changhong Huang, Wanjun |
| contents | The integration of intermittent renewable energy sources into distribution networks introduces significant uncertainties and fluctuations, challenging their operational security, stability, and efficiency. This paper considers robust distribution network reconfiguration (RDNR) with renewable generator resizing, modeled as a two-stage robust optimization (RO) problem with decision-dependent uncertainty (DDU). Our model optimizes resizing decisions as the upper bounds of renewable generator outputs, while also optimizing the network topology. We design a mapping-based column-and-constraint generation (C&CG) algorithm to address the computational challenges raised by DDU. Sensitivity analyses further explore the impact of uncertainty set parameters on optimal solutions. Case studies demonstrate the effectiveness of the proposed algorithm in reducing computational complexity while ensuring solution optimality. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_24677 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Robust Distribution Network Reconfiguration Using Mapping-based Column-and-Constraint Generation Zhang, Runjie Qu, Kaiping Zhao, Changhong Huang, Wanjun Systems and Control The integration of intermittent renewable energy sources into distribution networks introduces significant uncertainties and fluctuations, challenging their operational security, stability, and efficiency. This paper considers robust distribution network reconfiguration (RDNR) with renewable generator resizing, modeled as a two-stage robust optimization (RO) problem with decision-dependent uncertainty (DDU). Our model optimizes resizing decisions as the upper bounds of renewable generator outputs, while also optimizing the network topology. We design a mapping-based column-and-constraint generation (C&CG) algorithm to address the computational challenges raised by DDU. Sensitivity analyses further explore the impact of uncertainty set parameters on optimal solutions. Case studies demonstrate the effectiveness of the proposed algorithm in reducing computational complexity while ensuring solution optimality. |
| title | Robust Distribution Network Reconfiguration Using Mapping-based Column-and-Constraint Generation |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2505.24677 |