【摘要】 空调用能行为数据是住宅能耗预测与模拟的研究基础。常规的问卷调查、户外电表读取、电能计量仪以及温湿度计等实测方法为以往的研究提供了大量基础数据,但仍然不够理想。随着物联网的快速发展,集监测与控制于一体的智能家居设备逐步得到大众的认可与采用。该文通过对智能家居设备的调研与实测方法分析,提出基于智能家居设备来开展空调用能行为实测的3个技术支撑要素,5个用能行为关键绩效指标以及其在实测数量、时长、成本、精度和实时数据等方面的技术优势,希望为相关用能行为数据收集提供更多实测方法与创新思路。更多还原

【Abstract】 The large sample data of air-conditioning occupant behavior is the research basis for residential energy consumption prediction and simulation. Conventional questionnaires, outdoor meter reading, energy metering, and temperature and humidity measurements provide a lot of basic data for previous research, but they are still not ideal. With the rapid development of the Internet of Things, smart home devices that integrate monitoring and control have gradually gained recognition and adoption from the public. Based on the investigation and measurement plan analysis of smart home equipment, we propose three technical support factors for the measurement method of air-conditioning occupant behavior based on smart home equipment and its technical advantages in measured quantity, duration, cost and real-time data. We hope to provide more innovative ideas and methods for data collection of related energy use behaviors.更多还原