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 building practices and energy efficiency. The case studies demonstrate that selecting the right large language model techniques is essential to enhance performance and reduce engineering efforts. The findings advocate a multidisciplinary approach in future artificial intelligence research, with implications extending beyond building energy modeling to other specialized engineering modeling.

翻译：人工智能的快速发展促进了ChatGPT等大型语言模型的兴起，为专业工程建模（特别是基于物理的建筑能耗建模）提供了潜在应用前景。本文研究了大型语言模型与建筑能耗建模软件的创新性集成，重点探讨ChatGPT与EnergyPlus的融合应用。首先通过文献综述揭示了大型语言模型在工程建模中的应用日益增长的趋势，尽管其在建筑能耗建模领域的研究仍较为有限。我们强调大型语言模型在应对建筑能耗建模挑战方面的潜力，并概述了包括模拟输入生成、模拟输出分析与可视化、误差分析、联合仿真、模拟知识提取与训练以及模拟优化在内的潜在应用场景。三个案例研究揭示了大型语言模型在自动化和优化建筑能耗建模任务方面的变革潜力，凸显了人工智能在推进可持续建筑实践与能源效率方面的关键作用。案例研究表明，选择恰当的大型语言模型技术对于提升性能、降低工程工作量至关重要。研究结果主张未来人工智能研究应采取多学科交叉方法，其影响范围可超越建筑能耗建模领域，延伸至其他专业工程建模领域。