Digital Twin-Integrated Data-Driven Approach for Security Assessment in Modern Power Systems

Power grids are transitioning toward the smart grid paradigm to facilitate the incorporation of renewable energy sources (RESs) at an advanced stage. This transition is driven by environmental concerns, the imperative for decarbonization within contemporary power infrastructures, and the necessity to enhance energy security. Renewable energy resources, particularly those reliant on inverters such as photovoltaic panels and wind turbines, present novel challenges and technical complexities regarding the security of power systems. These energy sources substantially diminish the aggregate system inertia, thereby jeopardizing system stability. Similarly, the unpredictable nature of renewable resources engenders fluctuations in power generation, resulting in imbalances between supply and demand. Consequently, the security assessment of modern power grids is expected to become increasingly complex due to the significant integration of RESs and the widespread utilization of power electronic devices. Moreover, the emergence of various load types, such as electric vehicles, underscores the imperative for the advancement and deployment of robust and adaptable security assessment tools, such as AI-based algorithms.