Next Generation Data Management, Analytics, AI and Machine Learning to Power the Smart Utility
17-19 September 2019 | Berlin, Germany


Post Conference Seminar - AI & ML 4 Smart Grid Thursday 19 September 2019 Download
08:00Registration and refreshments
08:50Opening remarks from the chair
09:00Where to Start with AI – Determining how best to leverage AI and machine learning techniques on existing advanced analytics platforms to enable autonomous decision-making and portfolio optimization
09:40Centralised Grid Analytics – Developing the optimum methods to use multiple diverse data sources to your advantage in asset management
10:20Smart Dynamic Pricing - accessing flexibility from end-consumers through ML for different needs (e.g. balancing, congestion management, auto-consumption)
11:00Morning refreshments & exhibition
11:30Improving Safety with AI and ML – Using AI to monitor and assess worker safety during on-voltage operations
12:10Automated Asset Investment Planning – Using AI to find the most robust investment strategy for a system in transition
12:50Demand Response – Leveraging data analytics and machine learning for demand response
  • Miha Grabner - Milan Vidmar Electric Power Research Institute - Grid Asset Management 2019
    Miha Grabner
    Data Scientist, Milan Vidmar Electric Power Research Institute
13:30Lunch, network & exhibition
14:30Load Balancing – Developing a prognosis for consumption in trade using machine learning
15:10AI & ML for Smart Meter Data – Using smart meter data for distribution network monitoring and early warning of network constraints violation
  • Maizura Mokhtar - SP Energy Networks
    Maizura Mokhtar
    Data Scientist, KTP Associate, Heriot-Watt University and Scottish Power Energy Networks
15:50Wider AI Grid Applications – Using drones and AI recognition methods for asset management and examining the wider AI grid applications being evaluated at Enedis
  • Jean-Philippe Poirrier
    Jean-Philippe Poirrier
    Assistant Director, Smart Grid Solutions Industrialisation Program, Enedis
16:30Afternoon refreshments & exhibition
17:00AI Future Potential – Assessing the potential of AI for operating the grid under increasing uncertainty
  • Aidan O'Sullivan
    Aidan O’Sullivan
    Energy Systems and Data Analytics MSc, University College London
17:40AI for EV Charging: Quantifying and exploiting flexibility in EV charging with data-driven modeling and reinforcement learning
18:20End of seminar