AUTHOR=Cao Ge , Jia Rong , Dang Jian TITLE=Distributed Resilient Mitigation Strategy for False Data Injection Attack in Cyber-Physical Microgrids JOURNAL=Frontiers in Energy Research VOLUME=10 YEAR=2022 URL=https://www.frontiersin.org/journals/energy-research/articles/10.3389/fenrg.2022.845341 DOI=10.3389/fenrg.2022.845341 ISSN=2296-598X ABSTRACT=

The stable and reliable operation of microgrids requires the immediate communication and accurate measuring data of cyber systems. The cyber security of smart grids consists of detection and mitigation, where the latter mainly refers to resisting the attack and recovering the physical operation state through various means after cyber attacks. With the flexible electrical topology and the distributed control strategy based on the public communication network and end-to-end neighbor communication, the application and effect of cyber security technologies (firewall and encryption) in traditional cyber systems are limited. However, due to the fact that the cyber system and power system are coupled in microgrid cooperative control, countermeasures are added to the control to enhance the cyber security of microgrids, which has drawn more attention. Therefore, considering the control failure and even system results from the false data inject attack (FDIA) on the cooperative control of microgrids, this study investigates the synchronous mitigation framework based on local detection where the reactive power cooperative control targets of microgrids with and without FDIA are compatible by the resilient control method. The credibility is utilized to measure the reliability of local and neighbor data in the proposed method. The consensus communication coupling gain is weighted corrected by an adaptive update strategy of credibility to delete the attack signal. Moreover, the proposed method directly improves the conventional distributed secondary controller that reduces the complexity of controller design. Simulations investigate the effectiveness of the proposed distributed resilient mitigation strategy under conditions of deception and disruption attacks.