Open AccessResearch and Practice of Big Data Technology in Energy System
Author(s) -
Zhihui Ye,
Jie Qian,
Wenjuan Wang,
Dingke Shi,
Chen Li-feng
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/898/1/012003
Subject(s) - big data , computer science , process (computing) , data mining , energy (signal processing) , energy consumption , data acquisition , industrial engineering , engineering , mathematics , statistics , electrical engineering , operating system
The characteristics of the massive data is inspected which is accumulated by the energy management system of industrial enterprises during the production process. They are real-time, massive, non-linear, and even unstructured, meanwhile some implicit correlation are hidden between them. These correlations have not yet been fully learned and unearthed. Here big data technology is proposed to improve the availability of energy data for the energy saving and consumption reduction. The general pattern of big data application is proposed in energy management systems. On this basis, some algorithms are applied to the actual management process, including parameter prediction, status monitoring, operation optimization and performance evaluation. Finally, two practical examples of the constructed model are presented including compressed air prediction and Operation prediction of air-conditioning system. The results show that big data technology can improve the efficiency of data acquisition, expand data applications, and exert greater data value.