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Survey on Large Language Model-Enhanced Reinforcement Learning: Concept, Taxonomy, and Methods
With extensive pre-trained knowledge and high-level general capabilities, large language models (LLMs) emerge as a promising avenue to augment reinforcement learning (RL) in aspects such as multi-task learning, sample efficiency, and task planning.
Framework of Resilient Transmission Network Reconfiguration Considering Cyber-Attacks
Fast and reliable transmission network reconfiguration is critical in improving power grid resilience to cyber-attacks.
Adapting to climate change: Long-term impact of wind resource changes on China's power system resilience
Modern society's reliance on power systems is at risk from the escalating effects of wind-related climate change.
Applying Large Language Models to Power Systems: Potential Security Threats
Applying large language models (LLMs) to modern power systems presents a promising avenue for enhancing decision-making and operational efficiency.
Super-Resolution Perception for Industrial Sensor Data
In this paper, we present the problem formulation and methodology framework of Super-Resolution Perception (SRP) on industrial sensor data.
