Numerical Comparisons of Linear Power Flow Approximations: Optimality, Feasibility, and Computation Time
Not on the map. Why?
Abstract (arXiv)
Linear approximations of the AC power flow equations are of great significance for the computational efficiency of large-scale optimal power flow (OPF) problems. Put differently, the feasibility of the obtained solution is essential for practical use cases of OPF. However, most studies focus on approximation error and come short of comprehensively studying the AC feasibility of different linear approximations of power flow. This paper discusses the merits of widely-used linear approximations of active power in OPF problems. The advantages and disadvantages of the linearized models are discussed with respect to four criteria; accuracy of the linear approximation, optimality, feasibility, and computation time. Each method is tested on five different systems.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). First posted on arXiv 11 Jul 2022.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2024: 1; 2025: 1.
2 papers.
- 2024Beyond the Neural Fog: Interpretable Learning for AC Optimal Power Flowcited by 1
- 2025Revisiting Deep AC-OPFcited by 1
- 2025Revisiting Deep AC-OPF31 Aug 2025
- 2024Beyond the Neural Fog: Interpretable Learning for AC Optimal Power Flow30 Jul 2024