Design of indoor thermal comfort system based on wireless sensor network
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摘要: 为实现室内环境在保持热舒适状态的同时最大限度地减少能源消耗，设计一款基于无线传感器网络和简化预测平均热感觉(PMV)指数的室内热舒适系统。该系统采用散点布置法确定室内各传感器的最佳测量节点，采集的数据通过ZigBee通信传输到系统中，在系统中通过简化PMV指数评估室内环境的热舒适感知。最后，采用具有模糊性和非线性的模糊控制调控空调的运行。结果表明，散点布置的传感器收集的数据更加稳定准确，简化PMV指数可以有效替代PMV指数评估人体热舒适感知。热舒适系统不仅可以控制室内环境处于热舒适范围，同时也起到很好的节能效果。
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关键词:
- 无线传感器网络 /
- 散点布置法 /
- 简化预测平均热感觉指数 /
- 模糊控制 /
- 管理系统
Abstract: In order to minimize energy consumption while maintaining thermal comfort, an indoor thermal comfort system based on wireless sensor network and simplified predicted mean vote (PMV) index was designed. The scatter layout method was used to determine the best measurement nodes of indoor sensors, and the collected data was transmitted to the system through ZigBee communication. In the system, the thermal comfort perception of indoor environment was evaluated by simplified PMV index. Finally, fuzzy control with fuzziness and non-linearity was used to regulate the operation of the air conditioner. The results show that the data collected by the scatter sensor is more stable and accurate. Simplified PMV index can effectively replace the PMV index in evaluating human thermal comfort perception. The thermal comfort system can not only control the indoor environment within the thermal comfort range, but also play a good energy-saving effect. -
图 1 标准PMV和简化PMVs的相关性分析图
Figure 1. Correlation analysis diagram of standard PMV and simplified PMVs
图 7 手动调节与系统干预耗电量对比
Figure 7. Comparison of power consumption between manual adjustment and system intervention
表 1 标准PMV和简化PMVs值比较
Table 1. Comparison of standard and simplified PMVs values
采集时刻 计算结果 PMV PMVs 9:00 −0.18 −0.22 10:00 −0.09 0.02 11:00 0.15 0.09 12:00 0.19 0.15 13:00 0.37 0.36 14:00 0.47 0.44 15:00 0.45 0.41 16:00 0.32 0.29 17:00 0.21 0.20 平均值 0.21 0.19 标准方差 0.22 0.24 
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