Energy Consumption Prediction of Air-conditioning Based on SARIMA-GARCH Model

Chunli Kan; Qian Yu; Man Yang; Zhiyuan Hou; Hongwu Yuan

doi:10.6911/WSRJ.202507_11(7).0011

Authors

Chunli Kan
Qian Yu
Man Yang
Zhiyuan Hou
Hongwu Yuan

DOI:

https://doi.org/10.6911/WSRJ.202507_11(7).0011

Keywords:

Air-conditioning energy consumption prediction; SARIMA-GARCH model; Seasonal time series; Heteroscedasticity.

Abstract

Energy consumption prediction plays an important role in building design & retrofit, energy management system, but the nonlinear, dynamic and complex air-conditioning energy consumption data make it difficult. We employ SARIMA (Seasonal Autoregressive Integrated Moving Average) and GARCH (Generalized Autoregressive Conditional Heteroskedasticity) models respectively to extract the level and fluctuating information according to the trend, seasonality and random fluctuation of time series of energy consumption based on the real-time operation of air-conditioning in an office building, which are integrated to obtain a combined model of SARIMA(0,1,1)(1,1,1)₉-GARCH(1,2). The MAPE of SARIMA(0,1,1)(1,1,1)₉-GARCH(1,2) model is 4.46%.

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