Convex Relaxations and Linear Approximation for Optimal Power Flow in Multiphase Radial Networks
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Abstract (arXiv)
Distribution networks are usually multiphase and radial. To facilitate power flow computation and optimization, two semidefinite programming (SDP) relaxations of the optimal power flow problem and a linear approximation of the power flow are proposed. We prove that the first SDP relaxation is exact if and only if the second one is exact. Case studies show that the second SDP relaxation is numerically exact and that the linear approximation obtains voltages within 0.0016 per unit of their true values for the IEEE 13, 34, 37, 123-bus networks and a real-world 2065-bus network.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 11 Jun 2014.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 0; 2024: 0; 2025: 1; 2026: 1.
4 papers.
- 2022Learning Distribution Grid Topologies: A Tutorialcited by 3
- 2021Data-driven Modeling for Distribution Grids Under Partial Observabilitycited by 0
- 2025Power Flow Approximations for Multiphase Distribution Networks using Gaussian Processescited by 0
- 2026Toward Adaptive Grid Resilience: A Gradient-Free Meta-RL Framework for Critical Load Restorationcited by 0
- 2026Toward Adaptive Grid Resilience: A Gradient-Free Meta-RL Framework for Critical Load Restoration16 Jan 2026
- 2025Power Flow Approximations for Multiphase Distribution Networks using Gaussian Processes30 Apr 2025
- 2022Learning Distribution Grid Topologies: A Tutorial22 Jun 2022
- 2021Data-driven Modeling for Distribution Grids Under Partial Observability18 Aug 2021