Prediction of industrial power consumption in Jiangsu Province by regression model of time variable

被引:21
|
作者
Ma, Haoran [1 ]
机构
[1] Univ Shanghai Sci & Technol, Business Sch, Shanghai 200093, Peoples R China
关键词
Industrial power consumption; Time series; Nonlinear transformation; Forecast; FORECASTING ENERGY-CONSUMPTION; ELECTRICITY CONSUMPTION; GREY MODEL; ALGORITHM; EMISSION; DEMAND; ARIMA;
D O I
10.1016/j.energy.2021.122093
中图分类号
O414.1 [热力学];
学科分类号
摘要
Industry has always been an important driving force to promote social and economic development, and the development of industry is inseparable from energy consumption. In the process of modern production, more and more modern advanced equipment is put into use, and the main power source of these equipment is electricity. However, the production of electricity is limited by conditions. Therefore, the main purpose of this paper is to simulate and forecast the industrial power consumption of Jiangsu Province through the nonlinear transformation of time variables, so that the industrial enterprises in Jiangsu can reasonably arrange the next power demand and ensure the smooth progress of industrial activities. The final research results show that the time series regression prediction model proposed in this paper can effectively simulate and predict the results of industrial power consumption, with an accuracy of 1.02 %. (c) 2021 Elsevier Ltd. All rights reserved.
引用
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页数:5
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