airboxlab/rllib-energyplus
Simple EnergyPlus environments for control optimization using reinforcement learning
This tool helps building managers and energy engineers design smart control systems for buildings. It takes building simulation models (EnergyPlus files) and historical weather data, then helps optimize how heating, ventilation, and air conditioning (HVAC) systems operate to save energy while maintaining comfort. The output is an optimized control strategy that can be implemented in real buildings.
No commits in the last 6 months.
Use this if you need to develop and test advanced, AI-driven control strategies for building energy systems within a simulated environment.
Not ideal if you are looking for a plug-and-play solution for direct building management without needing to develop custom control algorithms.
Stars
55
Forks
9
Language
Python
License
MIT
Category
Last pushed
Jun 27, 2025
Commits (30d)
0
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