TY - JOUR
T1 - Big data driven smart energy management
T2 - From big data to big insights
AU - Zhou, Kaile
AU - Fu, Chao
AU - Yang, Shanlin
N1 - Publisher Copyright:
© 2015 Elsevier Ltd. All rights reserved.
PY - 2016/4/1
Y1 - 2016/4/1
N2 - Large amounts of data are increasingly accumulated in the energy sector with the continuous application of sensors, wireless transmission, network communication, and cloud computing technologies. To fulfill the potential of energy big data and obtain insights to achieve smart energy management, we present a comprehensive study of big data driven smart energy management. We first discuss the sources and characteristics of energy big data. Also, a process model of big data driven smart energy management is proposed. Then taking smart grid as the research background, we provide a systematic review of big data analytics for smart energy management. It is discussed from four major aspects, namely power generation side management, microgrid and renewable energy management, asset management and collaborative operation, as well as demand side management (DSM). Afterwards, the industrial development of big data-driven smart energy management is analyzed and discussed. Finally, we point out the challenges of big data-driven smart energy management in IT infrastructure, data collection and governance, data integration and sharing, processing and analysis, security and privacy, and professionals.
AB - Large amounts of data are increasingly accumulated in the energy sector with the continuous application of sensors, wireless transmission, network communication, and cloud computing technologies. To fulfill the potential of energy big data and obtain insights to achieve smart energy management, we present a comprehensive study of big data driven smart energy management. We first discuss the sources and characteristics of energy big data. Also, a process model of big data driven smart energy management is proposed. Then taking smart grid as the research background, we provide a systematic review of big data analytics for smart energy management. It is discussed from four major aspects, namely power generation side management, microgrid and renewable energy management, asset management and collaborative operation, as well as demand side management (DSM). Afterwards, the industrial development of big data-driven smart energy management is analyzed and discussed. Finally, we point out the challenges of big data-driven smart energy management in IT infrastructure, data collection and governance, data integration and sharing, processing and analysis, security and privacy, and professionals.
KW - Big data analytics
KW - Demand side management (DSM)
KW - Energy big data
KW - Smart energy management
KW - Smart grid
UR - https://www.scopus.com/pages/publications/84949494790
U2 - 10.1016/j.rser.2015.11.050
DO - 10.1016/j.rser.2015.11.050
M3 - 文献综述
AN - SCOPUS:84949494790
SN - 1364-0321
VL - 56
SP - 215
EP - 225
JO - Renewable and Sustainable Energy Reviews
JF - Renewable and Sustainable Energy Reviews
ER -