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Co-LLM: A retrieval-augmented language model framework for chiller optimization control
DOI:10.1016/j.jobe.2026.115683.png)
Abstract
En 中文
• Propose a Framework Co-LLM to enable real-time HVAC load optimization. • Introduce a selective re-calibration mechanism to fine-tune sensitive sub-policies. • Integrate RAG-tuned exploration policy retrieval with domain knowledge support. • Simulations on a hospital chiller plant show Co-LLM outperforms baseline methods.
Keywords:
Co-LLM
HVAC load optimization
selective re-calibration
RAG-tuned exploration
chiller optimization control
Journal
IF:
7.4
Papers:
1.6W
Citations:
6.6W

