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- W3186172313 abstract "With the rapid development of smart grid, the false data injection (FDI) attacks have grown to become one of the crucial threats faced by future power system operation. It is revealed that an attacker can significantly increase the loss of load demand (LoLD) of a power system by launching undetectable FDI attacks. Thus, it is necessary to establish a cost-effective mechanism for mitigating the LoLD against FDI attacks. In this paper, we develop a multi-objective cost-effective optimization model to make a trade-off between the least-budget defense costs to protect power system against FDI attacks and the least-LoLD to immune the possibility of power outage in dispatching. Then, a multiple preys-based evolutionary predator and prey strategy (MPEPPS) is presented to obtain the Pareto front that summarizes the compromise between the economic performance and the reliability factor of power system. The simulation results on the IEEE testing system verify the effectiveness of the proposed model and reveal that power system operation faces a high LoLD risk under FDI attacks." @default.
- W3186172313 created "2021-08-02" @default.
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- W3186172313 date "2021-11-01" @default.
- W3186172313 modified "2023-10-16" @default.
- W3186172313 title "Multi-objective cost-effective optimization for defending against false data injection attacks in power system operation" @default.
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- W3186172313 doi "https://doi.org/10.1016/j.epsr.2021.107469" @default.
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