Title: Energy big data management and analysis
Abstract: Smart metering technologies enable the collection and analysis of large-scale energy data from various sources, such as smart meters, renewable energy generation, and demand response programs. However, these data also pose significant challenges for data quality, privacy preservation, and data security. How can we manage and utilize energy data in a safe and efficient way? In this talk, I will give an overview of the state-of-the-art methods and techniques for energy data management and analysis. First, I will introduce a data intelligence platform that can handle heterogeneous and complex energy data using data lake and stream processing technologies. Second, I will present the research landscape of smart meter data analysis, and use data sharing as an illustrative example. The data sharing techniques employ data generative models to realize the data synthetics in terms of data statistics and semantics. Third, I will demonstrate how to apply a data synthesis technique to a federated learning framework in combination with differential privacy to train distributed models across multiple data sources so that it can preserve privacy without compromising data security. Finally, I will discuss the related challenges and future research directions for energy big data management and analysis. This talk will provide an overview of energy big data management and analysis, and elicit the novel solutions and insights for improving the efficiency, reliability, and sustainability of smart energy systems.
Biography. Dr. Xiufeng Liu is a senior researcher (Associate Professor level) at the Department of Technology, Management and Economics at the Technical University of Denmark (DTU). He specializes in smart meter data analysis, energy informatics, Big Data management and ETL. He has authored or co-authored more than 100 papers in prestigious energy and database journals and conferences, including Applied Energy, Energy, IEEE TSG, TII, TNNLS, EDBT, ICDE and TODS. He received the best paper award in EDBT 2015. Dr. Liu obtained his PhD in Computer Science from Aalborg University, Denmark, in 2012. He then worked as a postdoctoral researcher in the data systems
group at the University of Waterloo, Canada, and as a research scientist at IBM Toronto Research Center in 2013-2014. He joined DTU as a faculty member in 2015. He has been involved in, led or co-led over ten research projects funded by Danish Innovation Fund, European Horizon 2020, ERA-NET and Marie Curie Programs.