Verification of the accuracy of the Degree Day method using building simulation

In recent years, the increase in cooling demand due to global warming has become obvious, and there is concern about a rapid increase in energy demand associated with the rise in the number of air conditioners in the future. Currently, the Degree-Days (DD) method, which is based on outdoor temperature, is widely used to estimate cooling demand.

This method calculates energy demand by accumulating the difference between outdoor temperature and reference temperature when the outdoor temperature exceeds a set reference temperature as cooling degree-days. However, the DD method does not consider factors related to air conditioner operation, such as internal heat gains, solar gains, changes in COP (Coefficient of Performance) due to outdoor air temperature and part load factor, and latent heat load, which can lead to inaccuracies in estimation.

This study aims to provide a more accurate cooling energy consumption estimation method using the bottom-up simulation model. The simulation model estimates cooling demand by taking into account not only outdoor temperature but also building structure, occupant behavior patterns, and air conditioner performance characteristics. Utilizing meteorological data of Japan, we compared the results of cooling energy demand estimation by the simulation model with those of the DD method, clarifying the similarities and differences in demand increase trends in response to temperature rises.

The results showed that, during periods of high outdoor temperatures, the simulation model indicated an accelerated increase in cooling demand, whereas the DD method showed a linear increase, resulting in a significant discrepancy.

This research contributes to improving the accuracy of cooling demand estimates in the residential sector, aiming to enhance energy efficiency by matching supply with increasing demand.