IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids
21-24 October 2019 // Beijing, China

Call for Papers: Data Analytics and Computation

This symposium will consider how data can be collected and processed from the smart grid, energy internet, and related cyber-physical systems. Efficient data processing techniques for all kinds of power/energy data, including smart meters, phasor measurement unit measurements, grid status reports, and etc. should be discussed. Applications of data analytics to power/energy applications, such as demand response, demand-side management, predictive maintenance, and renewable energy management should be considered. Finally, the innovative use of artificial intelligence, machine learning and deep learning and data visualization approaches for the smart grid and energy internet 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
    • blockchain technologies
  • Big Data Analytics:
    • data mining, machine learning, and deep learning
    • privacy-preserving analytics
    • visualization
    • semantic techniques
    • real-time data analysis and decision making
    • cyber-physical modeling and simulation
  • Application of data management and analytics to:
    • power-grid transmission and distribution system automation
    • state estimation
    • energy internet and trading
    • resource aggregation (renewables, electric vehicles, flexible demand, etc.)
    • managing smart buildings/houses at scale
    • demand response
    • dynamic utility pricing
    • predictive maintenance
    • renewable energy management

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