A Bezier Curve Based Approach to the Convexification of the AC Optimal Power Flow Problem
Carlos Arturo Saldarriaga-Cortes, Carlos Adrian Correa-Florez, Maximiliano Bueno-Lopez, Maria Victoria Gasca-Segura

TL;DR
This paper introduces a novel convex reformulation of the AC optimal power flow problem using Bezier curves, enabling faster and more accurate solutions for complex power systems.
Contribution
It presents a new convexification method employing Bezier curves and logarithmic transformations, improving solution speed and accuracy for ACOPF problems.
Findings
Achieves convergence on large test systems within seconds.
Yields very low percentage errors in voltage magnitudes and angles.
Validated against exact AC solutions demonstrating high accuracy.
Abstract
The Alternating Current Optimal Power Flow (ACOPF) problem remains one of the most fundamental yet computationally challenging tasks in power systems operation and planning due to its nonconvex, nonlinear, and multimodal nature. This paper proposes a convex reformulation of the AC power flow problem by introducing auxiliary variables to isolate nonlinear terms, applying logarithmic transformations to exploit product-sum properties, and approximating with Bezier curves using a novel convexifying butterfly shaped function. This model is intended for assessing and operating weak power systems that face challenges with reactive power supply and overall network robustness. Its formulation closely mirrors the AC formulation, particularly regarding active and reactive power dispatch and network voltage levels. The proposed model achieves convergence on large test systems (e.g., IEEE 118 bus)…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsOptimal Power Flow Distribution · Power System Optimization and Stability · Electric Power System Optimization
