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CLC number: TP273
On-line Access: 2021-01-11
Received: 2020-04-30
Revision Accepted: 2020-10-10
Crosschecked: 2020-11-23
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Resilient distributed economic dispatch of a cyber-power system under DoS attack
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Feisheng Yang, Xuhui Liang, Xiaohong Guan. Resilient distributed economic dispatch of a cyber-power system under DoS attack[J]. Frontiers of Information Technology & Electronic Engineering, 2021, 22(1): 40-50.
@article{title="Resilient distributed economic dispatch of a cyber-power system under DoS attack",
author="Feisheng Yang, Xuhui Liang, Xiaohong Guan",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="22",
number="1",
pages="40-50",
year="2021",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2000201"
}
%0 Journal Article
%T Resilient distributed economic dispatch of a cyber-power system under DoS attack
%A Feisheng Yang
%A Xuhui Liang
%A Xiaohong Guan
%J Frontiers of Information Technology & Electronic Engineering
%V 22
%N 1
%P 40-50
%@ 2095-9184
%D 2021
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.2000201
TY - JOUR
T1 - Resilient distributed economic dispatch of a cyber-power system under DoS attack
A1 - Feisheng Yang
A1 - Xuhui Liang
A1 - Xiaohong Guan
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 22
IS - 1
SP - 40
EP - 50
%@ 2095-9184
Y1 - 2021
PB - Zhejiang University Press & Springer
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DOI - 10.1631/FITEE.2000201
Abstract: The economic dispatch problem of a smart grid under vicious denial of service (DoS) is the main focus of this paper. Taking the actual situation of power generation as a starting point, a new distributed optimization model is established which takes the environmental pollution penalty into account. For saving the limited bandwidth, a novel distributed event-triggered scheme is proposed to keep the resilience and economy of a class of cyber-power systems when the communication network is subject to malicious DoS attack. Then an improved multi-agent consensus protocol based on the gradient descent idea is designed to solve the minimization problem, and the prerequisites to minimize the system power generation cost are analyzed from the aspects of optimality and stability. Finally, the theoretical results are verified through a single-area 10-generator unit simulation.
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