Mitigation of severe false data injection attacks (FDIAs) in marine current turbine (MCT) type 4 synchronous generator renewable energy using promoted backstepping method

Hossein Mahvash, Seyed Abbas Taher and Josep M. Guerrero

Renewable Energy, 2024, vol. 222, issue C

Abstract: False data injection attack (FDIA) is kind of the most important and prevalent cyber attacks, influencing in power systems and renewable energy resources in microgrids (MGs). The destructive effects caused by FDIAs in the voltage components of synchronous generator with full converter in AC microgrid (ACMG) renewable energy production would seriously damage the DC link voltage, network frequency and also, the active power. The extracted voltage components in the d and q axes to control the grid side converter (GSC) as the main control section, are the important signals for power control process of the synchronous generator with wind or marine current turbine (MCT). In this regards and due to the nonlinear behavior caused by cyber attacks in the generator control process, the robust performance of modified nonlinear backstepping method would be an appropriate alternative, instead of the conventional linear control including PI controllers. Thus, a remedial action against various FDIAs caused in the voltage control commands of the GSC is proposed. Moreover, promotion of the backstepping control by combining with the switching terms, adopted from the higher order super twisting sliding mode control (HOSTSMC), the performance of the proposed method would be precisely robust. To verify the proposed method, severe FDIAs by injecting various constant values, periodic and also, noisy signals are our case studies which are simulated via MATLAB software in the weak grid connect and standalone operation modes.

Keywords: False data injection attack (FDIA); Grid side converter (GSC); DC link voltage; Active power; Marine current turbine (MCT); Renewable energy; Power management system (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:222:y:2024:i:c:s0960148124000739

DOI: 10.1016/j.renene.2024.120008

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