Power Consumption Forecast of Three Major Industries in China Based on Fractional Grey Model

Abstract

As one of the most significant carbon emission departments in China, the power industry will gradually become the core hub of reducing carbon emissions in the process of undertaking carbon emissions transferred from other industries. Therefore, it is of vital importance to predict the power consumption in China’s end energy consumption to achieve the carbon peak goal on time. This paper firstly uses the gray relational analysis model to study the relationship between power consumption indicators of the three major industries and some social and economic indicators and obtains the influencing factors with the greatest correlation with the power consumption of the three industries. Then, based on the analysis of socio-economic factors, considering different growth rates, the GMCN(1,N) model of electricity consumption in China’s three major industries is established. Forecast data under different scenarios have important practical significance for formulating active and effective energy policies. The data indicate that the secondary and tertiary industries consume the greatest amount of electricity. It is estimated that the power consumption of China’s three major industries will reach 10.15 trillion kWh (kilowatt hours) by 2030.

T-LGBKS: An Interpretable Machine Learning Framework for Electricity Consumption Forecasting

“…In recent years, China's economy has been under downward pressure. Influenced by multiple factors such as a tight electricity supply in some regions, increased demand for electricity in various industries, and the country's "double control" of energy consumption, the rise in electricity consumption has become more unpredictable [2]. In addition, as the largest carbon emitter, China has committed to achieving a carbon peak by 2030 and carbon neutrality by 2060, which implies a higher cost of electricity production [3].…”