4.6 Article

Time series forecasting on cooling degree-days (CDD) using SARIMA model

Journal

NATURAL HAZARDS
Volume 118, Issue 3, Pages 2569-2592

Publisher

SPRINGER
DOI: 10.1007/s11069-023-06109-4

Keywords

Cooling degree-days; Climate; Forecasting; SARIMA model

Ask authors/readers for more resources

Cooling Degree Days (CDD) is a technique that sums up the air temperature differences to quantify the deviation required for human comfort in summer. It is a useful tool for predicting cooling energy requirements in buildings. Accurate estimation of CDD trends is crucial for energy management and policy-making, and methods like SARIMA models can be used to forecast future values based on historical data. In this study, SARIMA models were used to forecast CDD values in high cooling demand regions in Turkey, indicating a slight increase in CDD values by 2031 due to global warming, which will impact building energy consumption policies.
Cooling Degree Days (CDD) is a convenient technique obtained by summing the cumulative air temperature differences that show how much deviation from the temperature is required for human comfort in a summer season. It is a basic and relatively simple measure for predicting the cooling energy requirements of the buildings. Accurate estimation of the seasonal trend of the CDD values is a crucial policy tool in determining the energy request for cooling the buildings and is critical to better energy management by decision-makers in the country. In this regard, planners or users need to develop appropriate and precise methods that allow them to forecast their future values based on their CDD historical time series data. For this reason, in this study, Seasonal Autoregressive Integrated Moving Average (SARIMA) model is utilized to forecast the CDD values in some regions with high cooling demand in Turkiye. To accomplish this, monthly CDD data from January 1991 to December 2022 are obtained from the provinces of Adana, Adyaman, Antalya, Siirt, and Sanlurfa. First, the CDD values are modeled using the SARIMA time series approach, and then the models are employed to predict the future trends of the CDD values from 2022 to 2031. Obtained results show that with the continuation of global warming at the current rate, CDD values in all selected provinces will increase slightly by 2031, which will cause a change in building energy consumption policies.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available