Data-driven p-norms for estimating transmission loss coefficients in power systems

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Authors: Oscar Danilo Montoya, Walter Gil-González, Luis Fernando Grisales-Noreña
Cited by: 2
References: 16

Abstract

This research introduces a novel convex methodology for estimating transmission loss coefficients (B-coefficients) in power systems using a data-driven approach based on power system measurements. To enhance estimation accuracy and practical relevance, the model is evaluated across a wide spectrum of operating conditions, incorporating random variations in active power injections and demand profiles modeled via uniform and Gaussian distributions. A semi-definite programming (SDP) model leveraging p-norm formulations is proposed to derive the B-coefficients efficiently. Numerical evaluations on IEEE 14-, 39-, 57-, and 118-bus test feeders demonstrate the effectiveness and robustness of the approach, yielding average estimation errors between [Formula: see text] and [Formula: see text] across diverse scenarios. These results confirm the reliability of the proposed methodology, contributing to improved accuracy in transmission loss modeling and supporting more efficient power system operations.

Fields of Study & Subjects

Power System Optimization and Stability Optimal Power Flow Distribution Electric Power System Optimization

Publication details

Journal / source
PLoS ONE
Publisher
Public Library of Science (PLoS)
Volume
21
Issue
3
Pages
e0345033–e0345033
Publication date
18 March 2026
Language
EN