Model-free HVAC control using occupant feedback
Model-free HVAC control using occupant feedback
复制标题
使用乘员反馈的无模型 HVAC 控制
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
Geoffrey Challen
中科院分区：
文献类型：
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作者：
Sean Purdon;Branislav Kusy;R. Jurdak;Geoffrey Challen
供暖、通风和空调（HVAC）的优化控制是减少建筑物碳足迹的重要一步，需要平衡能源减少和居住者舒适度。传统的温度设定值恒温器提供了一个集中的单点用户输入，经常导致严重的热不适的乘员。我们建议将用户纳入暖通空调控制回路，通过基于分布式智能手机的热舒适投票来实现暖通空调的综合控制。与现有的需要原位传感器或建立个人用户复杂舒适模型的方法不同，我们提出了一种无需模型和传感器的HVAC控制算法，该算法使用简单的用户输入（热/冷），并适应实时变化的办公室占用率或环境温度。我们开发了一种迭代数据融合算法，该算法可以在有多个用户的办公室中找到最佳温度，并提出了通过室内温度向室外温度漂移来大幅节省能源的技术。我们的评估是基于在3周内收集的12个办公室的经验数据，结果表明，自适应暖通空调控制可以节省高达60%的能源，而平均居住者的不适感只增加0.3°C。
Optimal control of Heating, Ventilation, and Air Conditioning (HVAC) is an important step towards reducing the carbon footprint of buildings and requires balancing energy reductions and occupant comfort. Conventional thermostats for temperature set points provide a centralised single point of user input, often leading to significant thermal discomfort for occupants. We propose to instead include users in the HVAC control loop through distributed smart-phone based votes about their thermal comfort for aggregated control of HVAC. Unlike existing approaches that require in-situ sensors or build complex comfort models of individual users, we propose a model- and sensor-free HVAC control algorithm that uses simple user input (hot/cold) and adapts to changing office occupancy or ambient temperature in real time. We develop an iterative data fusion algorithm that finds optimal temperature in offices with multiple users and propose techniques that can aggressively save energy by drifting indoor temperatures towards the outdoor temperature. Our evaluation is based on empirical data collected in 12 offices over a 3-week period and shows that adaptive HVAC control can save up to 60% of energy at a relatively small increase of 0.3°C in average occupant discomfort.