It is important to not only improve the performance of the building envelope and the efficiency of the equipment system but also to focus on occupants’ behavior to further promote energy conservation in buildings. In fact, the method called “Nudge, ” which has been applied in the field of behavioral science, is attracting attention as an energy-saving measure for buildings. Nudge is a system that alters people’s behavior in a predictable way without forbidding any options or significantly changing their economic incentives. Through information provision using Nudge, people can be encouraged to change their behavior to save energy.
In a large-scale experiment conducted in the US, the electricity consumption of households was reduced by approximately 2% on average as a result of providing information on electricity consumption compared with that of neighborhoods. It is thought that energy-saving behaviors are likely to occur because those behaviors directly lead to economic benefits for households. On the other hand, in public spaces such as offices and schools, the energy-saving effects may differ because occupants do not directly pay for utilities. In order to encourage energy conservation, it is important to promote initiatives that utilize information provision in office spaces. For this purpose, the impact of information provision on public spaces need to be verified, and the necessity of applying such measures must be clarified.
In previous research on occupants’ behavior, there are some examples in which the probability that occupants perform actions such as switching off lights and opening windows is modeled by logistic regression analysis. However, there are few examples on modeling the operation of automated office equipment. For further energy conservation, it is important to reduce wasteful consumption such as forgetting to turn off equipment upon leaving.
This paper proposes a method to model the operation of office equipment. Moreover, the energy-saving effects of information provision are evaluated using the model. The model was created by logistic regression analysis, and the data to determine the model parameters was obtained through an information provision experiment. The experiment was conducted in a laboratory as an example of a working space. In this paper, therefore, the operation of equipment by graduate students was modeled.
Modeling made it possible to calculate each subject’s probability of turning off the PC and Display when leaving the room using absent time as an explanatory variable. The degree to which behavioral change was caused by information provision varied greatly between subjects, and the results were not always positive. A simulation using the model showed that approximately 70% reduction in energy consumption could be achieved if all occupants changed their behavior as a result of information provision. However, considering the variations in the degree of behavioral change, it was possible to estimate that the total electricity consumption of the entire building could be reduced by several percent.
The proposed modeling method is expected to make it easier to grasp the characteristics of occupants’ behavior with regard to equipment operation, and contribute to strategic planning for information provision. In the future, a model will be developed that considers the fact that some people will not change their behavior even if information is provided. This is expected to improve the accuracy of predicting information provision effects by simulation.
