AutoB2G: A Large Language Model-Driven Agentic Framework For Automated Building-Grid Co-Simulation

1. 1Utilize reinforcement learning to learn control policies from building operational data
2. 2Implement a large language model-driven agentic framework for automated co-simulation
3. 3Evaluate grid-level impacts and building-side performance metrics systematically
4. 4Integrate AutoB2G with existing simulation environments to enhance experimental workflows

Data scientists and AI engineers on a team can benefit from AutoB2G as it enables automated co-simulation and evaluation of building-grid systems, while product managers can leverage it to optimize building performance and grid-level impacts

💡 AutoB2G enables automated co-simulation and evaluation of building-grid systems using reinforcement learning and large language models

🚀 AutoB2G: Automating building-grid co-simulation with large language models & reinforcement learning!