JUCS - Journal of Universal Computer Science 32(3): 337-356, doi: 10.3897/jucs.145075
OntoFreya: A Power Distribution Ontology for Electric Metrics Classification
Jorge Arthur Schneider Aranda‡§, Ricardo dos Santos Costa‡, Vitor Werner de Vargas‡, Paulo Ricardo da Silva Pereira‡, Jorge Luis Victória Barbosa‡, Marcelo Pinto Vianna|, Eleandro Luis Marques da Silva¶‡ University of Vale do Rio dos Sinos, São Leopoldo, Brazil§ Federal Institute of Education, Science and Technology, Veranópolis, Brazil| CEEE-D Power Utility, Porto Alegre, Brazil¶ Certaja Energy, Taquari, Brazil
Corresponding author: Jorge Arthur Schneider Aranda ( jorgearthurs@hotmail.com ) © Jorge Arthur Schneider Aranda, Ricardo dos Santos Costa, Vitor Werner de Vargas, Paulo Ricardo da Silva Pereira, Jorge Luis Victória Barbosa, Marcelo Pinto Vianna, Eleandro Luis Marques da Silva. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY-ND 4.0). This license allows reusers to copy and distribute the material in any medium or format in unadapted form only, and only so long as attribution is given to the creator. The license allows for commercial use. Citation:
Schneider Aranda JA, dos Santos Costa R, Werner de Vargas V, da Silva Pereira PR, Victória Barbosa JL, Pinto Vianna M, da Silva ELM (2026) OntoFreya: A Power Distribution Ontology for Electric Metrics Classification. JUCS - Journal of Universal Computer Science 32(3): 337-356. https://doi.org/10.3897/jucs.145075 |  |
Abstract
Power utilities demand large volumes of data used in power distribution networks. Among them are parameters representing possible technical failures, such as network’s short circuit current and voltage sag. Specialists find these parameters and detect technical failures. However, this process can become time-consuming. Thus, this article proposes an ontology called OntoFreya, which classifies voltage, current, or any electric metric, following the definitions of the regulatory agencies and reducing the time spent on this task. A series of 4402 axioms, 132 classes, and 40 data properties comprises OntoFreya. The ontology automatically inferred classifications for four hundred readings from energy samples, validating OntoFreya across three scenarios. The first and second scenarios classified current in amperes, and the third classified voltage in per-unit system (pu). The scenarios showed that OntoFreya automates the classification of electric metrics, reducing specialists’ time in detecting technical failures in a distribution network.
Keywords
Smart Grid, Ontology, Power Distribution, Artificial Intelligence