Forecasting of gas supply in self-provided power plant of iron and steel enterprises based on time series

3rd International Conference on Energy Engineering and Environmental Protection

能源学;生态环境科学

Meng, Hua^1^2 ; Fan, Guofeng^3

Chongqing Chemical Industry Vocational College, Chongqing

400020, China^1

University Electronic and Technology of China, Chengdu, SICHUAN

611731, China^2

Pingdingshan University, Pingdingshan, HENAN

467000, China^3

关键词: ARCH models;    Enterprise efficiency;    Forecast performance;    Iron and steel enterprise;    Optimal scheduling;    Reducing gas;    Sampling data;    Short-term forecasts;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/227/4/042008/pdf
DOI  :  10.1088/1755-1315/227/4/042008

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

The self-provided power plants are the main buffer customers for iron and steel industry. They have great effect on reducing gas emission and improving enterprise efficiency. The ARMA and ARMA-ARCH models are used to short-term forecast respectively based on sampling data, in order to master the varying trend of gas supply in iron and steel enterprises of self-provided power plants. The actual comparison and application results indicate that the ARMA-ARCH model has a well-pleasing forecast performance with a Mean Abs. Percent Error (MAPE) of 3.32%, plays an important role in adjusting boiler switches frequently and optimal scheduling in actual production.