Resilient Control of Smart Microgrids Based on Reliable Estimation

With the development of the times, the traditional power system can no longer meet the electricity demand of modern society, so through the deep integration of traditional power systems and modern sensing technology and communication technology, a new type of smart grid system has been formed. Although this has achieved efficient operation of power regulation, it also increases the complexity and openness of the power grid, making it face security issues of potential Cyber-physical attacks. The attacker can achieve no significant change in the output of the system through False Data Injection Attack(FDIA), and then deceive traditional chi-square tests based on the Kalman Filter. In order to solve the above problems, this paper adopts a new system framework that uses a Kalman Filter in the cloud and an Unknown Input Observer (UIO) locally. In this way when the system is attacked by stealthy attacks, the Unknown Input Observer can be used locally to control the system for a short period of time, eliminating the attacker's influence on the system. Finally the channel between local and cloud is protected by encryption using encrypted operators. At the same time, the encrypted operator can also strengthen the accuracy of attack detection. This paper verifies the effectiveness of the method based on this framework through simulation experiments.