Research Index

A novel framework combining multi-agent formation control and LLM-based reasoning for resilient microgrid management. The system uses distributed agents to maintain optimal power distribution while leveraging LLMs to diagnose faults, suggest recovery strategies, and adapt formation patterns for grid stability.

A novel approach combining digital twin technology with bio-inspired reinforcement learning to create self-healing protection systems for microgrids. The system learns from both simulated and real-world scenarios to adaptively optimize protection settings while maintaining grid stability, drawing inspiration from biological immune systems' ability to learn and adapt to new threats.