Review of Smart Meter Data Analytics: Applications, Methodologies, and Challenges

Abstract

The widespread popularity of smart meters enables an immense amount of\nfine-grained electricity consumption data to be collected. Meanwhile, the\nderegulation of the power industry, particularly on the delivery side, has\ncontinuously been moving forward worldwide. How to employ massive smart meter\ndata to promote and enhance the efficiency and sustainability of the power grid\nis a pressing issue. To date, substantial works have been conducted on smart\nmeter data analytics. To provide a comprehensive overview of the current\nresearch and to identify challenges for future research, this paper conducts an\napplication-oriented review of smart meter data analytics. Following the three\nstages of analytics, namely, descriptive, predictive and prescriptive\nanalytics, we identify the key application areas as load analysis, load\nforecasting, and load management. We also review the techniques and\nmethodologies adopted or developed to address each application. In addition, we\nalso discuss some research trends, such as big data issues, novel machine\nlearning technologies, new business models, the transition of energy systems,\nand data privacy and security.\n

Keywords

Affiliated Institutions

• University of North Carolina at Charlotte US
• Tsinghua University CN

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