期刊
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
卷 34, 期 8, 页码 4120-4129出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNNLS.2021.3123235
关键词
Power systems; Jamming; Adaptation models; Prediction algorithms; Load modeling; Frequency control; Power system stability; Data-driven; distributed model-free adaptive control (MFAC); jamming attack; load frequency control (LFC); predictive compensation algorithm
This article focuses on distributed resilient load frequency control (LFC) for multi-area power interconnection systems against jamming attacks. It proposes a model-free adaptive control (MFAC) model to handle uncertainties and high dimension nonlinearity in the power system. Additionally, a multistep predictive compensation algorithm is developed to mitigate the impact of jamming attacks. Simulation results demonstrate the effectiveness of the approach.
This article is concerned with distributed resilient load frequency control (LFC) for multi-area power interconnection systems against jamming attacks. First, considering uncertainties and high dimension nonlinearity, the model-free adaptive control (MFAC) model is adopted for the power system, in which only input and output (I/O) data are used. Second, jamming attacks are modeled in a stochastic process, and a multistep predictive compensation algorithm is developed to mitigate the impact of jamming attacks. Then, the distributed MFAC protocol with predictive compensation algorithm is designed such that the frequency tracking errors under the predictive compensation algorithm of multi-area power interconnection systems converge consensually into a small neighborhood of origin in the mean square sense. Simulation results show the effectiveness of the approach.
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