Distributed watermarking for secure control of microgrids under replay attacks

The problem of replay attacks in the communication network between Distributed Generation Units (DGUs) of a DC microgrid is examined. The DGUs are regulated through a hierarchical control architecture, and are networked to achieve secondary control objectives. Following analysis of the detectability of replay attacks by a distributed monitoring scheme previously proposed, the need for a watermarking signal is identified. Hence, conditions are given on the watermark in order to guarantee detection of replay attacks, and such a signal is designed. Simulations are then presented to demonstrate the effectiveness of the technique

Exploring Cyber Security Issues and Solutions for Various Components of DC Microgrid System

Nowadays, considering the growing demand for the DC loads and simplified interface with renewable power generation sources, DC microgrids could be cost effective solution for the power supply in small scale area. the supervisory control and data acquisition (SCADA) system maintain the bidirectional power communication through the internet connectivity with the microgrid. However, this intelligent and interactive feature may pose a cyber-security threat to the power grid. this work aims to exploring cyber-security issues and their solutions for the DC microgrid system. To mitigate the adverse effects of various cyber-attacks such as the False Data Injection (FDI) attack, Distributed Denial of Service (DDoS) attack etc., two new techniques based on non-linear and proportional-integral (PI) controllers have been proposed. Simulation results obtained from MATLAB/Simulink software demonstrate the effectiveness of the proposed methods in mitigating the adverse effects of cyber-attacks on the DCMG system performance

Reinforcing Data Integrity in Renewable Hybrid AC-DC Microgrids from Social-Economic Perspectives

The microgrid (MG) is a complicated cyber-physical system that operates based on interactions between physical processes and computational components, which make it vulnerable to varied cyber-attacks. In this paper, the impact of data integrity attack (DIA) has been considered, as one of the most dangerous cyber threats to MGs, on the steady-state operation of hybrid MGs (HMGs). Additionally, a novel method based on sequential hypothesis testing (SHT) approach, is proposed to detect DIA on the renewable energy sources’ metering infrastructure and improve the data security within the HMGs. The proposed method generates a binary sample, which is used to compute a test statistic that is further used against two thresholds to decide among three alternatives. The performance of the suggested method is examined using an IEEE standard test system. The results illustrated the acceptable performance of the proposed methodology in detection of DIAs. Also, to evaluate the effect of DIA on the operation of the HMGs, DIAs with different severities are launched on the measured power generation of renewable energy resources (RESs) like wind turbine (WT). The results of this part showed that a successful DIA on renewable units can severely affect the operation of electric grids and cause serious damages.© 2022 Copyright held by the owner/author(s), published by Association for Computing Machinery (ACM). This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in ACM Transactions on Sensor Networks, http://dx.doi.org/10.1145/3512891. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]=vertaisarvioitu|en=peerReviewed