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dc.contributor.authorChen, Jieen_US
dc.contributor.authorGallo, Alexander J.en_US
dc.contributor.authorYan, Shuoen_US
dc.contributor.authorParisini, Thomasen_US
dc.contributor.authorHui, Ron Shu-Yuenen_US
dc.identifier.citationChen, J., Gallo, A. J., Yan, S., Parisini, T. & Hui, R. S. (2022). Cyber-attack detection and countermeasure for distributed electric springs for smart grid applications. IEEE Access, 10, 13182-13192.
dc.description.abstractWith increasing installations of grid-connected power electronic converters in the distribution network, there is a new trend of using distributed control in a cyber layer to coordinate the operations of these power converters for improving power system stability. However, cyber-attacks remain a threat to such distributed control. This paper addresses the cyber-attack detection and a countermeasure of distributed electric springs (ESs) that have emerged as a fast demand-response technology. A fully distributed model-based architecture for cyber-attack detection in the communication network is developed. Based on a dynamic model of ES with consensus control, a local state estimator is proposed and practically implemented to monitor the system. The estimator is fully distributed because only local and neighboring information is necessary. A countermeasure for the distributed ESs to ride through the cyber-attack and maintain regulatory services in a microgrid is demonstrated successfully. Experimental results are provided to verify the effectiveness of the proposed cyber-attack detection method and its ride-through capability.en_US
dc.description.sponsorshipNanyang Technological Universityen_US
dc.relation.ispartofIEEE Accessen_US
dc.rights© 2022 The Author(s). Published by IEEE. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see
dc.subjectEngineering::Electrical and electronic engineeringen_US
dc.titleCyber-attack detection and countermeasure for distributed electric springs for smart grid applicationsen_US
dc.typeJournal Articleen
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.versionPublished versionen_US
dc.subject.keywordsElectric Springsen_US
dc.subject.keywordsCyber-Attack Detectionen_US
dc.description.acknowledgementThis work was supported in part by the Nanyang Technological University-MediaTek Endowment Fund in Singapore under Grant 03INS001124C140, in part by the European Union’s Horizon 2020 Research and Innovation Program under Grant 739551 (KIOS Centre of Excellence), and in part by the Italian Ministry for Research in the Framework of the 2017 Program for Research Projects of National Interest (PRIN) under Grant 2017YKXYXJ.en_US
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