Tutorial 2

 

Tutorial 2 Energy Internet: Concepts and Key Technologies
Presenters Professor Yan Zhang,  University of Oslo, Norway
Date and Time 22 May 2018, 08:00 am – 12:00 pm
Location  MR309
Details

Abstract

Energy Internet (or Internet of Energy, Energy Informatics) is a vision of future power systems, which will achieve highly efficient interconnection among various types of energy resources, storages, and loads and enable ubiquitous energy sharing on a large scale. The realization of Energy Internet requires deep integration of Internet of Things into smart energy systems.

In this tutorial, we will explain Energy Internet basic concepts, key enabling technologies, and our recent research results. We will first introduce the concepts, the main principle and architecture related to Energy Internet. Then, we will discuss on how state-of-the-art information technologies (e.g., fog computing, data analytics, machine learning, UAV) can be exploited in smart energy networks. Further, we will mainly focus on decentralized energy sharing and trading scenario. We will present on how blockchain, game theory and auction theory can be used for secure, privacy-preserving, and efficient energy sharing/trading. Demand response management, as a key enabling technology, will be explained to balance and shape the electricity demand and supply. In this context, we will mainly understand the effects of users’ demand, prices and electric vehicles. Finally, we will explain on how to explore machine learning in smart grid, in particular for renewable energy and energy price forecasting.

Tutorial Content

  • Energy Internet: overview
    • Basic concepts and Architectures
    • Key enabling technologies: overview
  • Energy Information Networks
    • Basic concepts, architectures
    • State-of-the-art information technologies for smart energy systems (e.g., fog computing, machine learning, UAV)
  • Distributed Energy Sharing and Trading
    • Definition and the main concepts
    • Demand Response Management: concept and main principles
    • Blockchain and Auction Theory for Secure and Efficient Distributed Energy Sharing
  • Machine Learning for Energy Forecasting
    • Machine learning for renewable energy forecasting
    • Machine learning for energy price forecasting
  • Conclusions and Q&A
Speaker’s Bio

Professor Yan Zhang is Full Professor in Department of Informatics at University of Oslo, Norway. He received a PhD degree from School of Electrical & Electronics Engineering, Nanyang Technological University, Singapore. He is an Associate Technical Editor of IEEE Communications Magazine, an Editor of IEEE Transactions on Green Communications and Networking, an Editor of IEEE Communications Surveys & Tutorials, an Editor of IEEE Internet of Things Journal, and an Associate Editor of IEEE Access. He served as 30+ guest editor in IEEE journals/magazines, including IEEE Transactions on Smart Grid, IEEE Transactions on Industrial Informatics, IEEE Transactions on Dependable and Secure Computing, IEEE Communications Magazines, IEEE Wireless Communications Magazine, IEEE Network Magazine, IEEE Access, IEEE Internet of Things journal, and IEEE Systems Journal. He serves as chair positions in a number of conferences, including IEEE GLOBECOM 2017, IEEE VTC-Spring 2017, IEEE PIMRC 2016, IEEE CloudCom 2016, IEEE CCNC 2016, IEEE SmartGridComm 2015, and IEEE CloudCom 2015. He serves as TPC member for numerous international conference including IEEE INFOCOM, IEEE ICC, IEEE GLOBECOM, and IEEE WCNC. His current research interests include: Energy Internet, Big Data (energy, wireless) and next-generation communications networks. He is IEEE VTS (Vehicular Technology Society) Distinguished Lecturer. He is also a senior member of IEEE, IEEE ComSoc, IEEE CS, IEEE PES, and IEEE VT society. He is a Fellow of IET.