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Credibility-based distributed frequency estimation for plug-in electric vehicles participating in load frequency control.
- Source :
-
International Journal of Electrical Power & Energy Systems . Sep2021, Vol. 130, pN.PAG-N.PAG. 1p. - Publication Year :
- 2021
-
Abstract
- • A large number of PEVs are participated in the distributed load frequency control. • A credibility based distributed frequency estimation scheme is presented to detect and isolate compromised PEVs. • A resilient distributed load frequency regulation is developed after the comprised PEVs are identified. The accurate, robust and economic acquisition of frequency signals of plug-in electric vehicles (PEVs) is a vital prerequisite to regulate the frequency of power systems with the participation of a large number of PEVs. While the communication links among PEVs are vulnerable to cyber attacks, we propose a credibility-based distributed frequency estimation scheme to detect and isolate compromised PEVs participating in the frequency regulation. In this scheme, each PEV can distinguish its neighbors' misbehavior based on the distributed frequency estimation and/or frequency measurements taken only at distribution substations. Then, a distributed load frequency control (DLFC) strategy is designed to integrate the credibility-based resilient distributed frequency estimation scheme. Tests under a variety of communication topologies are conducted to verify the proposed credibility-based distributed frequency estimation scheme. Simulation results of a four-area power system validate the proposed DLFC strategy after detecting and isolating the compromised PEVs can regulate the frequency quickly when suffering load variations. [ABSTRACT FROM AUTHOR]
- Subjects :
- *PLUG-in hybrid electric vehicles
*CYBERTERRORISM
*ELECTRICAL load
Subjects
Details
- Language :
- English
- ISSN :
- 01420615
- Volume :
- 130
- Database :
- Academic Search Index
- Journal :
- International Journal of Electrical Power & Energy Systems
- Publication Type :
- Academic Journal
- Accession number :
- 150083297
- Full Text :
- https://doi.org/10.1016/j.ijepes.2021.106997