Analysis of Occupants’ Air-Conditioning Opening Behaviour Based on the Survival Model

Abstract

It is essential to predict building energy consumption through more accurate simulation of building energy consumption, and then put forward suggestions for building energy conservation. Therefore, it is a very important issue to study the variable, random and complex air conditioning usage mode. In the previous studies on air conditioning, it could be found that whether the air conditioning is on or off, it is only a mathematical function about environmental parameters. However, when we arrive at the office and feel uncomfortable, we don't open the window immediately. Instead, we put up with it for a while. In view of the above shortcomings, this study proposed a survival model based on Weibull function to predict the air-conditioning on behavior. Through the verification of the model, we found that the accuracy of the air-conditioning regulation model based on the survival model is more than 74%. We compared and verified the common three-parameter Weibull model with the survival model-based Weibull model, and found that the accuracy of the common three-parameter Weibull model was slightly higher than that of the survival model. At the same time, we analyzed the death event (tolerance temperature) of the survival model, and further improving the tolerance temperature is of great help to the accuracy of the model.

Stochastic nature of occupants' behavior toward air‐conditioning operation in residential buildings

“…Ren et al. (2021) 23 applied a survival model for occupants' air‐conditioning use employing data collected in an office in Nanjing, China. Lyu et al.…”

“…Gunay et al (2017) 22 observed occupants' thermostat use at 37 office spaces located in Ottawa, Canada, and formulated a Markov logistic regression model. Ren et al (2021) 23 applied a survival model for occupants' air-conditioning use employing data collected in an office in Nanjing, China. Lyu et al (2022) 24 revealed the seasonal influence of occupants' air-conditioning-On action modeled by logistic equations based on a smart meter dataset collected at 586 Japanese dwellings.…”