Realization and Research of Intelligent system of client electricity information based on the Big Data Processing Technology
- DOI
- 10.2991/icadme-16.2016.110How to use a DOI?
- Keywords
- Big data, Data collection, Power information system, Software design, Intelligent clustering subsystem
- Abstract
Big data is the focus in power system currently. In order to analyze and classify the electricity model of clients, identify the avoiding peak space intelligently, extract value-added information of clients and control the electric load actively, it is extremely necessary to analyze the information of electricity clients and establish an intelligent system for electricity client information based on big data processing technology. A data collection method on client electricity information is proposed in this paper, which could be a security of client's electricity information. In order to improve the quality of data collection so as to consolidate the reliability of system information, distributed data processing platform based on Hadoop is designed to collect and process information of clients. On the basis of which, a software of intelligent system of client electricity information is designed as well, which consists of a series of intelligent clustering subsystems. The research results provide theoretical guidance for the application of big data processing technology in power system.
- Copyright
- © 2016, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Ming-Xin Wen AU - Ming-Hua Chu AU - Lei Fang AU - Wen-Jiao Chen PY - 2017/07 DA - 2017/07 TI - Realization and Research of Intelligent system of client electricity information based on the Big Data Processing Technology BT - Proceedings of the 2016 6th International Conference on Advanced Design and Manufacturing Engineering (ICADME 2017) PB - Atlantis Press SP - 629 EP - 632 SN - 2352-5401 UR - https://doi.org/10.2991/icadme-16.2016.110 DO - 10.2991/icadme-16.2016.110 ID - Wen2017/07 ER -