Rahman Dashti

Background: This research examines the efficiency and stability of DC microgrids in addressing challenges related to power sharing and threats posed by cyber-attacks. The aim of this study is to propose a method for improving the performance and security of microgrids under various operational conditions. Aim: The primary aim of this research is to propose a solution for detecting and correcting False data in DC microgrids to optimize power sharing and enhance the efficiency, stability, and security of these systems. Methodology: This research involves designing and implementing an algorithm for controlling power sharing and detecting cyberattacks in DC microgrids. It includes mathematical modeling of microgrids and decentralized controllers to optimize power distribution and detect false data. Additionally, computational techniques are used for attack detection and for assessing the impact of losses in transmission lines, with the aim of enhancing power management and security in microgrids. Conclusions: Simulation results demonstrate that the parity-based detection algorithm effectively identifies cyberattacks on DC microgrids with high accuracy and low false alarm rates. The algorithm performed well across three scenarios—attacks on actuators, sensors, and simultaneous attacks—proving its capability to detect unknown disturbances and utilize historical data to restore normal system operations. Overall, the algorithm significantly enhances the performance and security of DC microgrids by correcting false data, detecting and correcting cyberattacks and improving power sharing coordination among microgrids.