Reinforcing Data Integrity in Renewable Hybrid AC-DC Microgrids from Social-Economic Perspectives - Mohammadi, Mojtaba; Kavousi-Fard, Abdollah; Dehghani, Moslem; Karimi, Mazaher; Loia, Vincenzo; Haes Alhelou, Hassan; Siano, Pierluigi (Association for Computing Machinery, 2022)
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.
Keywords: Advanced Metering Infrastructure; Data Integrity; Hybrid Microgrids; Sequential Hypothesis Testing; renewable energy sources; fi=Sähkötekniikka|en=Electrical Engineering|