Resilient Model Free Adaptive Distributed LFC for Multi-Area Power Systems Against Jamming Attacks

作     者：Qiu, Xiaojie Wang, Yingchun Zhang, Huaguang Xie, Xiangpeng 

作者机构：Northeastern Univ State Key Lab Synthet Automat Proc Ind Shenyang 110004 Peoples R China Northeastern Univ Coll Informat Sci & Engn Shenyang 110004 Peoples R China Nanjing Univ Posts & Telecommun Inst Adv Technol Nanjing 210003 Peoples R China 

出 版 物：《IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS》 (IEEE Trans. Neural Networks Learn. Sys.)

年 卷 期：2023年第34卷第8期

页      面：4120-4129页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：National Natural Science Foundation of China [62173080, 62022044] Jiangsu Natural Science Foundation for Distinguished Young Scholars [BK20190039] 

主　　题：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 

摘      要：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.