TY - GEN
T1 - Smart grid data mining and visualization
AU - Zhou, Yingyao
AU - Li, Ping
AU - Xiao, Yuning
AU - Masood, Anum
AU - Yu, Qichen
AU - Sheng, Bin
PY - 2016/12
Y1 - 2016/12
N2 - The power industry innovation has increasingly become a top concern for current reforms. Power systems feature scattered data storage, incapable data analysis ability, poor computing capability, and ineffective interaction interface. To resolve these issues, we need multiple data mining techniques to extract information for analytical capacity improvement. Secondly, we need visualization techniques to analyze and optimize interaction. Lastly, we need distributed technologies for unified data management to increase computing capability and system scalability. Considering China's smart grid information, this paper proposes solutions to problems, such as the existing underdeveloped power management systems, a lack of automation methods, low data visualization, and poor data management. The electric power industry has functional requirements for this research. Based on existing data mining, visualization and understanding of distributed technologies, we discussed the functions of each part of the implementation in a smart grid management system: the data mining module, visualization module and data management module.
AB - The power industry innovation has increasingly become a top concern for current reforms. Power systems feature scattered data storage, incapable data analysis ability, poor computing capability, and ineffective interaction interface. To resolve these issues, we need multiple data mining techniques to extract information for analytical capacity improvement. Secondly, we need visualization techniques to analyze and optimize interaction. Lastly, we need distributed technologies for unified data management to increase computing capability and system scalability. Considering China's smart grid information, this paper proposes solutions to problems, such as the existing underdeveloped power management systems, a lack of automation methods, low data visualization, and poor data management. The electric power industry has functional requirements for this research. Based on existing data mining, visualization and understanding of distributed technologies, we discussed the functions of each part of the implementation in a smart grid management system: the data mining module, visualization module and data management module.
KW - Data mining
KW - Distributed computing
KW - Geographic information systems
KW - Smart grid
KW - Visualization
UR - http://www.scopus.com/inward/record.url?scp=85025126636&partnerID=8YFLogxK
U2 - 10.1109/PIC.2016.7949558
DO - 10.1109/PIC.2016.7949558
M3 - Conference article published in proceeding or book
AN - SCOPUS:85025126636
T3 - PIC 2016 - Proceedings of the 2016 IEEE International Conference on Progress in Informatics and Computing
SP - 536
EP - 540
BT - PIC 2016 - Proceedings of the 2016 IEEE International Conference on Progress in Informatics and Computing
A2 - Wang, Yinglin
A2 - Sun, Yaoru
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th IEEE International Conference on Progress in Informatics and Computing, PIC 2016
Y2 - 23 December 2016 through 25 December 2016
ER -