A Hybrid Sequential Convex Programming Framework for Unbalanced Three-Phase AC OPF
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arXiv
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| Hauptverfasser: | , |
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| Format: | Preprint |
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2025
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| _version_ | 1866909941884780544 |
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| author | Yehia, Sary Parisio, Alessandra |
| author_facet | Yehia, Sary Parisio, Alessandra |
| contents | This paper presents a hybrid Sequential Convex Programming (SCP) framework for solving the unbalanced three-phase AC Optimal Power Flow (OPF) problem. The method combines a fixed McCormick outer approximation of bilinear voltage-current terms, first-order Taylor linearisations, and an adaptive trust-region constraint to preserve feasibility and promote convergence. The resulting formulation remains convex at each iteration and ensures convergence to a stationary point that satisfies the first-order Karush-Kuhn-Tucker (KKT) conditions of the nonlinear OPF. Case studies on standard IEEE feeders and a real low-voltage (LV) network in Cyprus demonstrate high numerical accuracy with optimality gap below 0.1% and up to 2x faster runtimes compared to IPOPT. These results confirm that the method is accurate and computationally efficient for large-scale unbalanced distribution networks. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_03712 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Hybrid Sequential Convex Programming Framework for Unbalanced Three-Phase AC OPF Yehia, Sary Parisio, Alessandra Systems and Control This paper presents a hybrid Sequential Convex Programming (SCP) framework for solving the unbalanced three-phase AC Optimal Power Flow (OPF) problem. The method combines a fixed McCormick outer approximation of bilinear voltage-current terms, first-order Taylor linearisations, and an adaptive trust-region constraint to preserve feasibility and promote convergence. The resulting formulation remains convex at each iteration and ensures convergence to a stationary point that satisfies the first-order Karush-Kuhn-Tucker (KKT) conditions of the nonlinear OPF. Case studies on standard IEEE feeders and a real low-voltage (LV) network in Cyprus demonstrate high numerical accuracy with optimality gap below 0.1% and up to 2x faster runtimes compared to IPOPT. These results confirm that the method is accurate and computationally efficient for large-scale unbalanced distribution networks. |
| title | A Hybrid Sequential Convex Programming Framework for Unbalanced Three-Phase AC OPF |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2512.03712 |