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• W3204324352 abstract "• Derivation and solving methods of occupant behavior probability in buildings were proposed. • Several novel parameters were proposed for measuring occupant behaviors. • Quantitative models for predicting electricity consumption by occupant behaviors were proposed. • Quantitative models for predicting occupant numbers by environment and time were proposed. Energy consumption prediction for buildings and architectural complexes has become increasingly important. However, existing methods based on simulation software or statistical algorithms have distinct disadvantages. Consequently, this study introduces a novel prediction method based on models between occupant behavior and energy consumption. A new parameter––the occupant behavior characteristic parameter, is defined by coupling factors, including occupant behavior probability, occupant numbers, and building operation hours. Correlation models between this characteristic parameter ( Parameter A ) and electricity consumption ( Parameter B ) are established. Moreover, because of the difficulty in obtaining occupant numbers, models between environment, time influence factors ( parameter C ) and occupant numbers are proposed for occupant number prediction. In summary, models of the three parameters ( A , B , and C ) can be combined to obtain an electricity consumption prediction model. On the one hand, this model can reflect energy use laws with a higher accuracy than prediction methods based on temperature or other factors; on the other hand, it can be applied online without complex algorithms and software simulation. Moreover, it needs only model one equation for the same building types, which obviates modeling building-by-building like software simulation. Thus, the proposed model offers strong operability, especially the prediction for architectural complexes." @default.
• W3204324352 created "2021-10-11" @default.
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• W3204324352 date "2021-12-01" @default.
• W3204324352 modified "2023-09-29" @default.
• W3204324352 title "Quantitative correlation models between electricity consumption and behaviors about lighting, sockets and others for electricity consumption prediction in typical campus buildings" @default.
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• W3204324352 doi "https://doi.org/10.1016/j.enbuild.2021.111510" @default.
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