ChatGPT in passive energy-saving technologies: Opportunities and challenges

This study explores the support and application of passive energy-saving technologies at different stages through querying ChatGPT on passive energy-related questions. The research findings reveal that during the background information retrieval stage, ChatGPT rapidly provides accurate climate characteristics, building status, and other relevant data, thereby enhancing the ease and speed of adopting passive energy-saving technologies. In the design strategy formulation stage, ChatGPT offers various passive energy-saving strategies, expanding the breadth of technological development. Furthermore, in the performance simulation stage, ChatGPT envisions the benefits of energy conservation, cost reduction, and improved indoor comfort, thereby enhancing the depth of energy-saving technology development. However, the application of ChatGPT also faces particular challenges. Concerning data accuracy, ChatGPT’s responses rely on the accuracy of its training data, which may lead to potential issues if the data is unreliable. Additionally, as ChatGPT’s reactions tend to be more generalized for specialized questions, there is room for improvement in the precision and comprehensiveness of the information provided. Furthermore, ChatGPT cannot offer real-time updated data, warranting attention to its practicality.