Characterization of Distribution Systems Topological Flexibility using Bipartite Multigraphs

Abstract

Over recent decades, power distribution systems have been required to handle extreme events that are increasing in both frequency and intensity. In addition, there are novel technologies, planning strategies, and operational approaches. In this context, topological flexibility is a key aspect to allow distribution systems to accommodate all the simultaneous emerging changes and requirements. Topological flexibility is the capability of a system to rearrange its structure and is directly related to sectionalizing and tie switches operation. In this paper, metrics calculated from a bipartite multigraph representation aiming to describe the topological flexibility of distribution systems are presented. Different distribution systems are used to illustrate the bipartite graph representation and the derived metrics. Our approach is directly applicable to distribution systems characterization and enables future development of metrics to fully describe the topological flexibility of such systems.

Publication DOI: https://doi.org/10.20906/cba2022/3425
Divisions: College of Engineering & Physical Sciences > School of Computer Science and Digital Technologies > Applied AI & Robotics
College of Engineering & Physical Sciences > School of Computer Science and Digital Technologies
College of Engineering & Physical Sciences
Additional Information: This is an accepted manuscript of an article published in Procedings do Congresso Brasileiro de Automática. The published version is available at: https://doi.org/10.20906/CBA2022/3425
Uncontrolled Keywords: Modeling and Simulation of Power Systems,Power Distribution Systems,Complex Adaptive Systems,Topological Flexibility,Bipartite Graphs
Publication ISSN: 2525-8311
Last Modified: 16 Jan 2024 14:48
Date Deposited: 29 Nov 2023 16:53
Full Text Link:
Related URLs: https://sba.org ... ticle/view/3425 (Publisher URL)
PURE Output Type: Conference article
Published Date: 2022-10-19
Accepted Date: 2022-10-01
Authors: Bessani, Michel
de S. Batista, Lucas
Campelo, Felipe (ORCID Profile 0000-0001-8432-4325)

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