Recently, the Essential Science Indicators (ESI) database released the latest highly influential papers. The paper "Review of Smart Meter Data Analytics, Methodologies, and Challenges published on IEEE Transactions on Smart Grid was selected as both a highly cited paper and a hot paper in ESI, the first author of this paper is Wang Yi, a doctoral student of EEA (now a postdoctoral fellow of Swiss Federal Institute of Technology in Zurich), the second author is Chen Qixin, an associate professor long employed by EEA, the correspondence author is Professor Kang Chongqing of EEA, and Professor Hong Tao of the University of North Carolina at Charlotte is an major collaborator of this paper.

Since it was officially published in 2019, this paper has been cited 116 times in the Web of Science, ranking 0.135%, and 362 times in Google Scholar. Citing authors come from more than 20 countries, including the United States, Canada, United Kingdom, France, Germany, Italy, Switzerland, Denmark, Greece, Finland, Portugal, Japan, India, Indonesia, Saudi Arabia and so on. In addition, the paper has been at the forefront of popular papers in the IEEE Transactions on Smart Grid since it was published.

The paper "Review of Smart Meter Data Analytics: Applications, Methodologies, and Challenges" is supported by the National Key R&D program "Basic Theory of Power System Planning and Operation with High Renewable Energy Incorporated". As China is comprehensively advancing digitalization, how to convert data into effective information and effectively support real-time monitoring and decision-making for energy systems, is an issue which needs to be explored in the fields of power and energy. With the advancement of digitalization, smart electricity meters are also being applied extensively, and comprehensive analysis of electricity consumption data has become a hotspot in global research, the core of which is to mine the value of smart meter measurement, so as to carry out targeted auxiliary decision-making, improve electricity consumption efficiency, promote the consumption of renewable energy and reduce carbon emissions.

This paper summarizes and prospected the analysis methods of global smart electricity consumption data in detail. It comprehensively summarizes the typical applications of smart electricity consumption data by three ways of load analysis, load forecast and load management, and studied the intelligent electricity consumption data in topology analysis, power failure management, data compression and data privacy. Finally, it analyzes the orientation of future research on smart electricity consumption data by ways of data fusion and computing, new machine learning technology, new business model, energy structure transformation, data privacy and security. Moreover, this paper also introduces the work of EEA in fields of electricity consumption data compression, electricity consumption behavior analysis, user portrait description, electricity consumption bad data identification, probabilistic load forecast and so on.

Smart electricity data application framework

It is learned that ESI Top Papers mainly include two types: One is Highly Cited Papers, which refer to papers published in the last 10~11 years and ranked in the top 1% of times of being cited according to the statistics of the same ESI discipline in the same year; the other is Hot Papers, which refers to the papers published in the last two years and ranked in the top 0.1% of times being cited in the last two months according to statistics of the ESI discipline.

Link to the original papers

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