Abstract
Several ontologies have been developed for the detection of failures in electric power systems. However, these ontologies have been developed for specific aspects of the electricity grid and do not consider the necessary elements for the representation of a fault detection system based on Smart Grid trends. In this paper, we describe the development process of EPFDO, an ontology composed of a network of ontologies that allow the representation of intelligent system elements. EPFDO includes Sensors cases, Electrical Demand Management, Geographical Location, Operations, among other aspects that make EPFDO a more useful system for researchers who may have a standard for fault detection according to domain requirements.
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References
WGS84 Geo Positioning: an RDF vocabulary (2007)
Bernaras, A., Laresgoiti, I., Bartolome, N., Corera, J.: An ontology for fault diagnosis in electrical networks. In: Proceedings of International Conference on Intelligent System Application to Power Systems, pp. 199–203 (1996). https://doi.org/10.1109/ISAP.1996.501068
Brickley, D., Miller, L.: FOAF Vocabulary Specification 99 (2014)
Cuenca, J., Larrinaga, F., Curry, E.: A unified semantic ontology for energy management applications, vol. 1936, pp. 86–97 (2017)
Dalianis, H., Persson, F.: Reuse of an ontology in an electrical distribution network domain. In: Proceedings of the AAAI 1997 Spring Symposium Series, Ontological Engineering, pp. 25–32 (1997)
Daniele, L., Solanki, M., den Hartog, F., Roes, J.: Interoperability for smart appliances in the IoT world. In: Groth, P., et al. (eds.) ISWC 2016. LNCS, vol. 9982, pp. 21–29. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-46547-0_3
Das, S., Bhowmik, S., Giri, C.: End device energy optimization in ASPL for semantic sensor network, pp. 1–6. IEEE, India (2017). https://doi.org/10.1109/ANTS.2017.8384148. https://ieeexplore.ieee.org/document/8384148
García-Duarte, D., Leiva-Mederos, A., Galvez-Lio, D.: Electric power fault detection: ontolgy (2019). www.semanticweb.org/doymer/ontologies/2019/11/red
Gillani, S., Laforest, F., Picard, G.: A generic ontology for prosumer-oriented smart grid. In: 3rd Workshop on Energy Data Management at 17th International Conference on Extending Database Technology, Greece (2014). https://hal-emse.ccsd.cnrs.fr/emse-00948316
Haase, P., et al.: The NeOn ontology engineering toolkit. In: WWW 2008 Developers Track (2008). https://www.aifb.kit.edu/web/Inproceedings1757
Huang, Y., Zhou, X.: Knowledge model for electric power big data based on ontology and semantic web. CSEE J. Power Energy Syst. 1(1), 19–27 (2015). https://doi.org/10.17775/CSEEJPES.2015.00003. Conference Name: CSEE Journal of Power and Energy Systems
Kofler, M.J., Reinisch, C., Kastner, W.: A semantic representation of energy-related information in future smart homes. Energy Build. 47, 169–179 (2012). https://doi.org/10.1016/j.enbuild.2011.11.044. http://www.sciencedirect.com/science/article/pii/S0378778811005901
Kolozali, S., Bermudez, M., Barnaghi, P.: Stream Annotation Ontology (2016)
Kucuk, D., Salor, O., İnan, T., Cadirci, I., Ermis, M.: PQONT: a domain ontology for electrical power quality. Adv. Eng. Inform. 24(1), 84–95 (2010)
Lin, H., Tang, W.H., Ji, T.Y., Wu, Q.H.: A novel approach to power transformer fault diagnosis based on ontology and Bayesian network, pp. 1–6. IEEE (2014)
Liu, L., Zu, X., Xu, R.: Multi-agent system coordination architecture and its use in electric power decision support system, pp. 731–736. IEEE (2008)
Noy, N.F., Musen, M.A.: Algorithm and tool for automated ontology merging and alignment. In: Proceedings of the 17th National Conference on Artificial Intelligence (AAAI 2000). Available as SMI technical report SMI-2000-0831, vol. 115. AAAI (2000)
OCG, W.: Semantic Sensor Network Ontology (2017)
Padron Hernández, S.: Inteligencia artificial en la operación de redes eléctricas. Aplicación a sistemas aislados. Ph.D. thesis, Universidad de Las Palmas de Gran Canaria (2015)
Pezeshki, H., Wolfs, P., Johnson, M.: Multi-agent systems for modeling high penetration photovoltaic system impacts in distribution networks. In: 2011 IEEE PES Innovative Smart Grid Technologies, pp. 1–8, November 2011. https://doi.org/10.1109/ISGT-Asia.2011.6167149
Poveda Villalon, M.: Ontology evaluation: a pitfall-based approach to ontology diagnosis. Ph.D. thesis, Universidad Politecnica de Madrid, Escuela Tecnica Superior de Ingenieros Informaticos (2016)
Puebla-Martínez, M.E., Perea-Ortega, J.M., Simón-Cuevas, A., Romero, F.P.: Automatic expansion of spatial ontologies for geographic information retrieval. In: Medina, J., et al. (eds.) IPMU 2018. CCIS, vol. 854, pp. 659–670. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-91476-3_54
Radulovic, F., Poveda-Villalón, M., Vila-Suero, D., Rodríguez-Doncel, V., García-Castro, R., Gómez-Pérez, A.: Guidelines for Linked Data generation and publication: an example in building energy consumption. Autom. Constr. 57, 178–187 (2015)
Samirmi, F.D., Tang, W., Wu, H.: Power transformer condition monitoring and fault diagnosis with multi-agent system based on ontology reasoning. In: 2013 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC), pp. 1-6 (2013). ISSN: 2157-4847
Samirmi, F.D., Tang, W., Wu, Q.: Fuzzy ontology reasoning for power transformer fault diagnosis. Adv. Electr. Comput. Eng. 15(4), 107–114 (2015). https://doi.org/10.4316/AECE.2015.04015
Santofimia, M.J., del Toro, X., Roncero-Sánchez, P., Moya, F., Martinez, M.A., Lopez, J.C.: A qualitative agent-based approach to power quality monitoring and diagnosis. Integr. Comput. Aided Eng. 17(4), 305–319 (2010)
Santos, G.J.L.d.: Ontologies for the interoperability of multiagent electricity markets simulation platforms. Ph.D. thesis (2015)
Santos, J., Braga, L., Cohn, A.G.: Engineering time in an ontology for power systems through the assembling of modular ontologies, pp. 255–258 (2010)
Stavropoulos, T.G., Vrakas, D., Vlachava, D., Bassiliades, N.: BOnSAI: a smart building ontology for ambient intelligence. In: Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics, WIMS 2012, pp. 1–12. Association for Computing Machinery, New York, June 2012. https://doi.org/10.1145/2254129.2254166
Suárez-Figueroa, M.C.: NeOn Methodology for building ontology networks: specification, scheduling and reuse. Ph.D. thesis, Informatica (2010)
Wang, D., Tang, W.H., Wu, Q.H.: Ontology-based fault diagnosis for power transformers. In: IEEE PES General Meeting, pp. 1–8, July 2010. https://doi.org/10.1109/PES.2010.5589575. iSSN 1944-9925
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Mederos, A.L., García-Duarte, D., Lio, D.G., Hidalgo-Delgado, Y., Ruíz, J.A.S. (2020). An Ontological Model for the Failure Detection in Power Electric Systems. In: Villazón-Terrazas, B., Ortiz-Rodríguez, F., Tiwari, S.M., Shandilya, S.K. (eds) Knowledge Graphs and Semantic Web. KGSWC 2020. Communications in Computer and Information Science, vol 1232. Springer, Cham. https://doi.org/10.1007/978-3-030-65384-2_10
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