Prediction of Energy Consumption Based on Grey Model - GM (1,1)

The prediction of energy consumption plays an important role in energy management system of enterprise. This paper presents an algorithm of grey model-GM(1,1) to forecast the energy consumption of enterprise. In this article, the principle of grey prediction is analyzed and grey model- GM(1,1) is established, at the same time, the validation of method is verified by making use of the sampled data of compressed air consumption from steel workshop. The average relative error of grey model-GM(1,1) is no more than 1%. The result shows that grey model-GM(1,1) has higher prediction precision and the trend of energy consumption can be reflected accurately in actual energy consumption forecasting.

Authors and Affiliations

1. School of Automation Science and Electrical Engineering, Beijing University of Aeronautics and Astronautics, Beijing, China

   Xiuli Yu & Zhen Lu

Editors and Affiliations

1. School of Computer and Information Engineering, Shanghai University of Electric Power, 200090, Shanghai, China

   Jingsheng Lei

2. Deaprtment of Business Administration, Caritas Institute of Higher Education, 18 Chui Ling Road, Tseung Kwan O, Hong Kong, China

   Fu Lee Wang

3. School of Business Information Technology and Logistics, RMIT University, City Campus, 124 la Tobre Street, 3000, Melbourne, Victoria, Australia

   Hepu Deng

4. School of Electronics and Information, Tongji University, 201804, Shanghai, China

   Duoqian Miao

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