An online algorithm for linear optimal power flow computations

Galeano-Suarez, D., Toquica, D., Henao, N., Agbossou, K. et Oviedo-Cepeda, J. C. (2025). An online algorithm for linear optimal power flow computations. Dans PEET 2025 - Proceedings of 2025 International Conference on Power Engineering and Electrical Technology DOI 10.1109/PEET65412.2025.11341409.

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Résumé

The conventional optimal power flow (OPF) formulation falls short when dealing with incomplete information in real-time operations. Recent studies propose OPF reformulations using online algorithms to cope with this limitation. However, existing implementations oversimplify grid models, resulting in noticeably unrealistic scenarios. This study employs a linear approximation of the power flow balance equation that convexifies the problem while preserving reactive power flows and voltage variables within the analysis. Thus, the OPF is formulated as an online convex optimization problem and solved using primaldual updates. This study presents the update equations using the Lagrangian function that minimizes the dynamic regret. The proposed algorithm is tested on the IEEE 33-bus test system to validate its convergence and analyze application opportunities. The results demonstrate that the algorithm converges with sublinear regret and fulfills the OPF security constraints.

Type de document:	Document issu d'une conférence ou d'un atelier
Mots-clés libres:	Distribution power systems Online algorithm Optimal Power Flow Regret minimization
Date de dépôt:	25 mai 2026 18:52
Dernière modification:	25 mai 2026 18:52
Version du document déposé:	Post-print (version corrigée et acceptée)
URI:	https://depot-e.uqtr.ca/id/eprint/12898

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