Large Language Models for HVAC Operations in Building Energy Systems: A Critical Review of Methods, Applications, and Deployment Readiness

Alexander Neubauer, Tianzhen Hong, Han Li, Mengbo Yu, Amin Darbandi et al.|September 4, 2026arXiv

Key Takeaway

LLMs for building HVAC are research-stage tools best suited for semantic and workflow support (naming, documentation, operator guidance), not autonomous control—conventional ML and model predictive control remain more reliable for actual operational decisions.

Summary

This review examines 66 studies on using large language models for HVAC building control systems. While LLMs show promise for semantic tasks like naming conventions and operator support, the research remains largely theoretical—only 4 studies reached pilot stage and none achieved real operational deployment.

applications safety evaluation

Key Terms

model-predictive-control building-energy-modelling human-in-the-loop semantic-layer