Load Shedding

Load shedding, the intentional interruption of electricity supply to maintain grid stability during emergencies, aims to prevent widespread blackouts by balancing supply and demand. Current research heavily emphasizes developing real-time, equitable load shedding strategies using machine learning, particularly neural networks, to overcome the computational challenges posed by large-scale power systems. These methods focus on decentralized control and efficient algorithms to enable millisecond-level decision-making, improving grid resilience and minimizing disruptions. This work has significant implications for enhancing power grid reliability and ensuring fair distribution of load shedding across different regions.