Research Index

A novel framework combining large language models with hybrid energy storage systems (batteries, hydrogen, supercapacitors) to optimize energy dispatch and storage allocation. The system uses LLMs to analyze weather patterns, market conditions, and historical data to make intelligent storage decisions while incorporating non-linear control techniques for real-time optimization.

A novel framework integrating large language models with microgrid control systems for intelligent predictive maintenance and resource optimization. The system combines natural language processing of maintenance logs, sensor data analysis, and reinforcement learning to create self-healing power networks that can anticipate failures and automatically adjust resource allocation.

A novel system that combines LLM-based multi-agent systems with wireless power transfer networks to create resilient, self-optimizing power distribution systems. The system continuously adapts to failures, misalignments, and changing power demands while maintaining optimal efficiency through intelligent agent coordination.

A novel framework combining wireless power transfer technology with multi-agent LLM systems to create self-healing, adaptive energy distribution networks. The system uses AI to optimize power transfer paths, predict equipment failures, and automatically reroute energy flow while maintaining system stability under various attack scenarios.