Conference Paper

Proceedings of SimBuild Conference 2024

Advancing Building Energy Modeling with Large Language Models: Exploration and Case Studies

Liang Zhang ¹, Zhelun Chen ², Vitaly Ford ³, Peng Xu ^4
1 University of Arizona, United States of America
² Drexel University, United States of America
³ Arcadia University, United States of America
⁴ Tongji University, China

Abstract: The rapid progression in artificial intelligence has facilitated the emergence of Large Language Models (LLMs) like ChatGPT, offering potential applications extending into building energy modeling (BEM). This paper investigates the innovative integration of LLMs with BEM tools, focusing specifically on the fusion of ChatGPT with EnergyPlus. A literature review reveals a growing trend of incorporating LLMs in engineering modeling, albeit limited research on their application in BEM. We underscore the potential of LLMs in addressing BEM's challenges and outline potential applications such as input generation. Through case studies, we demonstrate the transformative potential of LLMs in revolutionizing the BEM lifecycle.
Keywords: large language model, ChatGPT, building energy modeling, EnergyPlus
Pages: 441 - 453
Paper: