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Advancing Building Energy Modeling with Large Language Models: Exploration and Case Studies by Zhang, Liang; Chen, Zhelun; Ford, Vitaly is a scholarly article available to read on EtoBox.
What is Advancing Building Energy Modeling with Large Language Models: Exploration and Case Studies about?
The rapid progression in artificial intelligence has facilitated the emergence of large language models like ChatGPT, offering potential applications extending into specialized engineering modeling, especially physics-based building energy modeling. This paper investigates the innovative integration of large language models with building energy modeling software, focusing specifically on the fusion of ChatGPT with EnergyPlus. A literature review is first conducted to reveal a growing trend of incorporating large language models in engineering modeling, albeit limited research on their application in building energy modeling. We underscore the potential of large language models in addressing building energy modeling challenges and outline potential applications including simulation input generation, simulation output analysis and visualization, conducting error analysis, co-simulation, simulation knowledge extraction and training, and simulation optimization. Three case studies reveal the transformative potential of large language models in automating and optimizing building energy modeling tasks, underscoring the pivotal role of artificial intelligence in advancing sustainable buil
- Author
- Zhang, Liang; Chen, Zhelun; Ford, Vitaly
- Published
- 2024
- Language
- EN
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