Modeling and Evaluating Power Grid Resilience Under Extreme Space Weather

The geomagnetically induced current (GIC) produced during extreme geomagnetic storms can easily lead to large-scale blackouts in China due to the increase in the scale of its electric power grid. A power grid's resilience is its capability to resist various natural hazards, withstand primary failures, and quickly resume normal operation. To avoid power grid damages, this study developed a resilient power grid, incorporating failure, power flow calculation and recovery models under a uniform induced geoelectric field. We chose a system's performance loss as the resilience evaluation indicator, which intuitively reflected a system's loss under GIC. In addition, the recovery model was optimized using a genetic algorithm, and two resilience improvement measures were proposed. The IEEE-RTS-79 system, consisting of 10 generators, 24 buses and 5 transformers, was chosen as an example to verify the feasibility of this study. The results show that the genetic algorithm and optimization measures effectively enhanced the system's resilience indicator and provided a reference for preventing system damages under GIC and quick recovery after possible failures. Extreme space weather produces large geomagnetic field disturbances; these disturbances propagate down to Earth, inducing secondary geomagnetically induced currents (GICs) in earthed electric power grids. GICs increase transformers' reactive power loss and raise their temperatures; this affects a power system's normal operation, and in extreme cases causes major blackouts. Therefore, it is vital to study power grids' resilience under GIC events. In this study, we calculated the GIC level using a uniform geoelectrical conductivity model. Based on this, we proposed a resilient power grid model consisting of the failure model, power flow calculation model and recovery model, and evaluated optimization strategies. Our results show that the proposed model can improve a power system's recovery performance after possible failure due to GICs and effectively avoid GIC-related large-scale blackouts. We proposed a resilience assessment method for transmission systems under extreme space weatherWe calculated a resilience indicator and identified multiple effective methods to improve a system's resilienceWe chose the IEEE-RTS-79 system as an example to verify the effectiveness of a genetic algorithm and optimization measures