在办公楼的开放空间中对HVAC系统控制进行网络支持的优化
Bo Peng1, Sheng-Jen Hsieh1,2
1Mechanical Engineering, Texas A&M University, College Station, TX 77840, USA.
Sensors (Basel, Switzerland)
|July 11, 2023
概括
这项研究介绍了办公楼的数据驱动的热舒适模型,在不增加能源使用的情况下,提高乘客舒适度高达69.93%. 混合网络物理系统模型为更好的室内环境提供了适应性控制.
科学领域:
- 建筑科学 建筑科学
- 环境控制系统环境控制系统
- 人类建设互动互动互动
背景情况:
- 人类的热舒适对于福祉和生产力至关重要,主要由供暖,通风和空调 (HVAC) 系统管理.
- 当前的HVAC控制指标和传统的舒适度模型往往过于简单化,无法适应个体需求,无法准确调节室内气候.
- 现有的系统缺乏个性化,导致办公环境中的热条件不足.
研究的目的:
- 开发和评估数据驱动的热舒适模型,以提高办公楼内乘客舒适度.
- 利用网络物理系统 (CPS) 架构来适应和精确控制室内热环境.
- 调查模型对乘客舒适度和建筑能耗的影响.
主要方法:
- 在网络物理系统 (CPS) 架构中集成的混合,数据驱动的热舒适模型的开发.
- 创建一个建筑模拟模型,以复制在开放空间办公室环境中的各种居住者行为.
- 验证模型的预测准确性和性能,以改善舒适度和提高能源效率.
主要成果:
- 混合模型在合理的计算时间内准确预测乘客的热舒适度.
- 观察到乘客热舒适度的显著改善,从43.41%到69.93%不等.
- 能源消耗保持稳定或略有下降 (1.01%至3.63%),同时提高了热舒适度.
结论:
- 开发的数据驱动的热舒适模型有效地提高了办公楼中乘客的舒适度.
- 网络物理系统方法可以实现自适应控制,解决传统舒适模型的局限性.
- 该战略显示了在现实世界的建筑自动化系统中实际实施的潜力,优化了舒适度和能源使用.
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