Climate change would affect the building energy demand in the future. Building simulation is a feasible way to quantitatively evaluate this impact. Based on the long/short-term climate periodicity analysis, a Dual-Periodic Time Series Model is established to predict the future monthly temperatures in Shanghai. From the fitting results and the preliminary assessment analysis, it is observed that the alternative forecasting method and the corresponding Dual-Periodic TSM has better capability of characterizing and predicting performance for both recent and future temperature trends in Shanghai than GCM under RCP4.5. With consideration of three composite uncertainty scenarios, we convert the predicted monthly temperatures into hourly TMYs by using Morphing method. Using the future TMYs as the weather input of prototypical building models of Shanghai, we can see that the simulated building energy demand presents fluctuant trends in the future periods.
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