IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids
29 Oct - 1 Nov 2018 // Aalborg, Denmark

Data Analytics and Computation

Co-chairs:

1. Emre Can Kara - (emrecan@slac.stanford.edu) – Stanford University, USA

2. Manish Marwah - (manish.marwah@gmail.com) – Hewlett Packard Laboratories, USA

3. György Dán - (gyuri@kth.se), Kungliga Tekniska Högskolan, SE

 

This symposium will consider how data can be collected and processed from the smart grid and related cyber-physical systems. Efficient data processing techniques for all kinds of smart grid data, including smart meters, phasor measurement unit measurements, grid status reports, etc should be discussed. Applications of data analytics to smart grid applications, such as demand response and demand side management should be considered. Finally, the innovative use of artificial intelligence, machine learning and deep learning and data visualization approaches for the smart grid in a variety of contexts including efficient network management, improved situational awareness and anomaly detection will be of interest.

Topics of interest include, but are not limited to the following:

  • Data management strategies:
    • Strategies for wide-area monitoring and visualization
    • software/cloud architectures
    • reliable and privacy-preserving data storage
    • reliable and privacy-preserving data communications
  • Big Data Analytics:
    • data mining, machine learning and deep learning
    • privacy-preserving analytics
    • visualization
    • semantic techniques
    • real-time data analysis and decision making
  • Application of data management and analytics to:
    • power-grid transmission and distribution system automation
    • state estimation
    • energy trading
    • resource aggregation (renewables, electric vehicles, flexible demand, etc.)
    • managing smart buildings/houses at scale
    • demand response
    • dynamic utility pricing

The organizers particularly welcome case studies based on real-world data.