Big data driven smart energy management: From big data to big insights. (April 2016)

• Record Type: Journal Article
• Authors: Zhou, Kaile; Fu, Chao; Yang, Shanlin
• Is Part Of: Renewable & sustainable energy reviews. Volume 56(2016:Apr.)
• Page Start: 215
• Page End: 225
• Publication Date: 2016-04
• Subjects: Energy big data -- Smart energy management -- Big data analytics -- Smart grid -- Demand side management (DSM); Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.rser.2015.11.050
• Languages: English
• ISSNs: 1364-0321

Abstract

Abstract: 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.