A Linear AC-OPF Formulation for Unbalanced Distribution Networks

Journal Article (2021)
Author(s)

Juan S. Giraldo (University of Twente)

Pedro P. Vergara (TU Delft - Intelligent Electrical Power Grids)

Juan Camilo Lopez (University of Campinas)

Phuong H. Nguyen (Eindhoven University of Technology)

Nikolaos G. Paterakis (Eindhoven University of Technology)

Research Group
Intelligent Electrical Power Grids
Copyright
© 2021 Juan S. Giraldo, P.P. Vergara Barrios, Juan Camilo Lopez, Phuong H. Nguyen, Nikolaos G. Paterakis
DOI related publication
https://doi.org/10.1109/TIA.2021.3085799
More Info
expand_more
Publication Year
2021
Language
English
Copyright
© 2021 Juan S. Giraldo, P.P. Vergara Barrios, Juan Camilo Lopez, Phuong H. Nguyen, Nikolaos G. Paterakis
Research Group
Intelligent Electrical Power Grids
Issue number
5
Volume number
57
Pages (from-to)
4462-4472
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

Linear optimal power flow (OPF) formulations are powerful tools applied to a large number of problems in power systems, e.g., economic dispatch, expansion planning, state estimation, congestion management, electricity markets, among others. This article proposes a novel mixed-integer linear programming formulation for the ac-OPF of three-phase unbalanced distribution networks. The model aims to minimize the total energy production cost while guaranteeing the network's voltage and current magnitude operational limits. New approximations of the Euclidean norm, which is present in the calculation of nodal voltage and branch current magnitudes, are introduced by applying a linear transformation of weighted norms and a set of intersecting planes. The accuracy, optimality, feasibility, and scalability of the proposed linearizations are compared with common linear approximations in the literature using two unbalanced distribution test systems. The obtained results show that the proposed formulation is computationally more efficient (almost twice) while being as accurate and more conservative than the benchmarked approaches with maximum errors lower than 0.1%. Thus, its potential application in a variety of distribution systems operation and planning optimization problems is endorsed.

Files

License info not available