Recently, the IEEE Power and Energy Society (IEEE PES) released the result of the 2021 IEEE Transactions on Smart Grid Outstanding Papers. The paper “Review of Smart Meter Data Analytics: Applications, Methodologies, and Challenges” published by the Smart Energy Research Group of the Department of Electrical Engineering and Applied Electronics won the outstanding paper and ranked first among the 5 ranked papers. The outstanding paper authors come from more than ten universities and national laboratories around the world, and Tsinghua University is the only institution in the Chinese mainland. “IEEE Smart Grid Transactions” is a top academic journal in the field of electricity and energy, and one of the academic journals with the highest influence factor in this field. The average influence factor in the past five years has exceeded 10, which has significant academic influence.

The research in this paper was carried out with the support of the National Key R&D Program “Basic Theory of Power System Planning and Operation for High-Proportion Renewable Energy Grid Incorporated Power System”. Under the background of China’s comprehensive promotion of digitalization, how to convert data into effective information and provide strong support for real-time monitoring and decision-making of energy systems is an issue that needs to be fully explored in the field of power and energy. With the continuous advancement of energy system digitalization, smart meters are also becoming more and more popular, and comprehensive analysis of electricity consumption data has become a hotspot of global research, because its core is to dig out the value of data measurement by smart meters, provide targeted assistant in decision making, improve the efficiency of electricity consumption, and promote the consumption of renewable energy and reduce carbon emissions.

This paper makes an all-around summary and outlook about the global methods for analyzing big data on smart electricity. It comprehensively summarizes the typical applications of big data on smart power consumption in three major branches, load description, load prediction and load prescription, and nine sub-branches. In addition, it also analyzes the most updated research on big data of smart electricity in topology analysis, power outage management, data compression, and data privacy. Finally, it looks forward to the future research on big data of smart electricity from the perspective of big data fusion and computing, new machine learning technology, new business model, energy structure transformation, data privacy and security. Furthermore, it also introduces the work of the Department of Electrical Engineering and Applied Electronics on power consumption data compression, power consumption behavior analysis, user portrait drawing, power failure data identification, and probabilistic load prediction.

Applications of big data on smart electricity consumption

The first author of this paper is Wang Yi, a doctoral student of the Department of Electrical Engineering of Applied Electronics (currently an assistant professor at the University of Hong Kong), the second author is Chen Qixin, a tenured associate professor of the Department of Electrical Engineering and Applied Electronics, and the corresponding author is Professor Kang Chongqing of the Department of Electrical Engineering and Applied Electronics, and one of the co-authors is Professor Hong Tao of University of North Carolina at Charlott (an alumnus of Tsinghua University). Previously, this paper was also selected as ESI highly cited paper and hotspot paper.

With 24 pages in total, this paper is the longest paper published in the history of IEEE Transactions on Smart Grid. Since it was officially published in 2019, it has been cited for more than 260 times in Web of Science and more than 600 times in Google Scholar. The authors of the citing documents come from more than 20 countries, including the United States, Canada, the United Kingdom, France, Germany, Italy, Switzerland, Denmark, Greece, Finland, Portugal, Japan, India, Indonesia, Saudi Arabia and China. In addition, since the paper was published, it has been at the forefront of the popular papers in the IEEE Transactions on Smart Grid.

Since the inception of IEEE Transactions on Smart Grid, it has been the first time to select outstanding papers from papers published in the past three years (September 2018 to August 2021), finally five papers were selected, and the selection rate was less than three in one thousand.

Link to the original paper

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

https://ieeexplore.ieee.org/document/8322199

Link to the original report:

https://site.ieee.org/pes-enews/2022/01/20/ieee-transaction-on-smart-grid-tsg-outstanding-papers-reviewers-and-associate-editors-for-the-year-2021/