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Analysis of historical and future cooling degree days over Türkiye for facade design and energy efficiency in buildings
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AbstractIn today’s examination of optimal facade design for buildings, facade performance has a significant influence on cooling energy consumption. Cooling degree days (CDD) is regarded as a basic and straightforward approach for predicting building cooling energy consumption. Accurate seasonal trend forecasting of the CDD plays a vital role in estimating the energy demand for building cooling. Unfortunately, there are no published statistics or research on Turkey’s CDD data for the following years. The monthly mean CDD data of Türkiye were created in this study utilizing data from the Turkish State Meteorological Service for the historical period from 1991 to 2022. The Seasonal Autoregressive Integrated Moving Average (SARIMA) approach was used to model the CDD data, and a time series forecast was performed. The SARIMA model was used to forecast the future trend of CDD from 2023 to 2040. The monthly and yearly CDD statistics were presented as figures, while the yearly CDD maps for Türkiye were created using the ArcGIS software program. Finally, CDD zones that require more attention to the most appropriate facade design in terms of energy efficiency for buildings in Türkiye were identified and classified.
Springer Science and Business Media LLC
Title: Analysis of historical and future cooling degree days over Türkiye for facade design and energy efficiency in buildings
Description:
AbstractIn today’s examination of optimal facade design for buildings, facade performance has a significant influence on cooling energy consumption.
Cooling degree days (CDD) is regarded as a basic and straightforward approach for predicting building cooling energy consumption.
Accurate seasonal trend forecasting of the CDD plays a vital role in estimating the energy demand for building cooling.
Unfortunately, there are no published statistics or research on Turkey’s CDD data for the following years.
The monthly mean CDD data of Türkiye were created in this study utilizing data from the Turkish State Meteorological Service for the historical period from 1991 to 2022.
The Seasonal Autoregressive Integrated Moving Average (SARIMA) approach was used to model the CDD data, and a time series forecast was performed.
The SARIMA model was used to forecast the future trend of CDD from 2023 to 2040.
The monthly and yearly CDD statistics were presented as figures, while the yearly CDD maps for Türkiye were created using the ArcGIS software program.
Finally, CDD zones that require more attention to the most appropriate facade design in terms of energy efficiency for buildings in Türkiye were identified and classified.
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