用EnergyPlus快速模拟房间温湿度等环境数据，助力建筑智能研究。
EnergyPlus Room Simulator
- 基于EnergyPlus构建房间级气候仿真工具，支持温度/湿度/二氧化碳等参数模拟。
- 提供图形界面与REST API，显著提升仿真效率和数据获取便捷性。
- 适合做建筑能耗优化、人员行为识别等任务的预训练数据生成。
建筑节能优化研究高度依赖室内气候等实测数据，但数据采集成本高。模拟是低成本生成大规模数据的有效替代方案，尤其适用于深度学习方法。本文提出EnergyPlus Room Simulator工具，利用EnergyPlus软件实现对建筑特定房间内气候条件的仿真，可调整房间模型并模拟温度、湿度、二氧化碳浓度等因子。相比手动操作EnergyPlus，该工具通过友好的图形界面（GUI）和REST API，显著提升仿真流程效率。其设计旨在支持科研与建筑相关任务，如基于房间级别的人员检测，通过快速获取仿真数据，为机器学习模型提供预训练支持。
原文摘要 · Abstract (English)
Research towards energy optimization in buildings heavily relies on building-related data such as measured indoor climate factors. While data collection is a labor- and cost-intensive task, simulations are a cheap alternative to generate datasets of arbitrary sizes, particularly useful for data-intensive deep learning methods. In this paper, we present the tool EnergyPlus Room Simulator, which enables the simulation of indoor climate in a specific room of a building using the simulation software EnergyPlus. It allows to alter room models and simulate various factors such as temperature, humidity, and CO2 concentration. In contrast to manually working with EnergyPlus, this tool enhances the simulation process by offering a convenient interface, including a user-friendly graphical user interface (GUI) as well as a REST API. The tool is intended to support scientific, building-related tasks such as occupancy detection on a room level by facilitating fast access to simulation data that may, for instance, be used for pre-training machine learning models.
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