针对HVAC系统的优化知情规则提取:在混合潮湿气候区的专用户外空气系统控制的案例研究.
Youngsik Choi1, Xing Lu1,2, Zheng O'Neill1
1J. Mike Walker '66 Department of Mechanical Engineering, Texas A&M University, College Station, TX, United States.
通过规则提取优化专用室外空气系统 (DOAS),节省能源并改善室内空气质量. 这种基于模拟的方法为建筑操作员提供了实用,可实施的控制序列.
科学领域:
- 暖通空调系统工程 HVAC系统工程
- 建筑物的能源效率.
- 室内环境质量 室内环境质量
背景情况:
- 专门的室外空气系统 (DOAS) 对于在COVID-19后保持室内空气质量至关重要,因为它可以提供100%的新鲜空气.
- 目前的DOAS控制策略往往缺乏实际指导,导致通风不足,除湿和能源浪费等问题.
- 对于建筑设计师和运营商来说,现有的先进控制可能过于复杂.
研究的目的:
- 开发一个基于模拟的框架,用于为DOAS生成可实现的供应空气温度控制序列.
- 优化DOAS控制,以节省能源和在建筑物中的实际应用.
- 确保提高节能潜力,同时保证控制逻辑的可执行性.
主要方法:
- 在EnergyPlus中模拟了美国能源部的原型小学,包括带有能量回收和风扇线圈单元的DOAS.
- 采用基因算法来确定最佳的供应空气温度控制序列,以最大限度地降低HVAC能源成本.
- 利用决策树分析从最佳控制序列中提取实际操作规则.
主要成果:
- 基于优化规则的提取控制与传统控制相比,大约节省了13%的能源成本和25%的能源消耗.
- 节能主要是由于减少了供暖能耗.
- 开发的控制策略接近于最佳的控制性能,以减少复杂性实现显著的能源减少.
结论:
- 使用优化和规则提取的基于模拟的框架可以产生高效和可实现的DOAS控制序列.
- 这种方法为提高建筑物的能源效率和室内空气质量提供了切实可行的解决方案.
- 基于优化的规则提取为建筑设计师和操作人员提供了控制性能和操作简单性之间的平衡.
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