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Hierarchical control of AC microgrids, despite providing stable voltage, frequency, and optimal power distribution, is susceptible to false data injection (FDI) attacks on its secondary control. Electric power systems in countries such as the United States and Venezuela have suffered cyberattacks. This paper proposes a redundant secondary control method to resist FDI attacks. This method uses distributed generators (DGs) online as redundant units on standby, generating dynamic corrections to the attacked DGs, thus eliminating the attack impact. It effectively addresses the numerical tampering and addition brought by FDI to the frequency and voltage setting values of the secondary control, ensuring the microgrid can still output stable frequency and voltage. The principle of this control method is direct and practical; it does not require complex controllers and can respond quickly to FDI attacks. Then, focusing on a microgrid system containing six DGs, the setting values of the microgrid system are tampered with by multiple values in different time periods, the simulation results confirm that the proposed method can effectively resist FDI attacks under various scenarios. Finally, field programmable gate array (FPGA)-in-the-loop experiments further verify the effectiveness of the proposed method.

Power control and optimization are both crucial for the proper operation of a microgrid. However, in existing research, they are usually studied separately. Active and reactive powers are either maintained to constant values at device level or optimized at system level without considering frequency and voltage control of distributed converters. In this article, a holistic power control and optimization strategy is proposed for microgrids. Specifically, a model predictive control incorporated with the droop method is developed at device level to achieve load sharing and flexible power dispatching among distributed energy resources, which is feasible for both islanded and grid-connected modes. In addition, an evolutionary particle swarm optimization algorithm is designed at system level to generate the optimal active and reactive power setpoints, which are then sent to the device level for controlling inverters. The proposed power optimization scheme is able to mitigate voltage deviations and minimize the operational cost of the microgrid. Comprehensive case studies and real-time simulator test are provided to demonstrate the feasibility and efficacy of the proposed power control and optimization strategy. [ABSTRACT FROM AUTHOR]