Controlling Commercial Cooling Systems with Reinforcement Learning
A technical paper by DeepMind, Google, and Trane on controlling commercial-building chiller plants using reinforcement learning (RL). The authors describe BCOOLER, a system that generates safe recommendations for setpoints and equipment configurations based on BMS data, energy-use forecasts, and operating constraints. In real-world A/B experiments at two sites, the system reduced energy consumption by 9% and 13%, respectively, compared with Trane’s heuristic Sequence of Operations (SOO).
Reinforcement LearningAI-based HVAC controlChiller plantsData center cooling
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