Presentation given on the 3rd of December 2018 in Paris, at the event where I was awarded by the SEE the prestigious Blondel Medal for my research work. This presentation gives a brief overview of the work I have carried out over these last twenty years.

1. A glimpse at the research work of the
laureate of the Blondel Medal 2018
Prof. Damien ERNST
Soirée des Grands Prix SEE

2. MISSO
Transmission
network (TN)
Distribution
network
(DN)
DN
DN
Advanced decision-
making strategies
implemented
Fit and Forget doctrine
The electrical grid as it used to be

3. F&F doctrine too conservative for keeping pace
with the rise of renewables and new electricity uses

4. Active Network Management
Smart modulation of generation sources, loads and storages
so as to safely operate the electrical network without
having to rely on significant investments in infrastructure.

5. 1. Interaction models
2. Investments
3. Operational planning
4. Real-time control
Decision chain in distribution networks
The four stages of the decision chain for managing distribution
networks:

6. Our integrated approach for designing ANM

7. www.blacklight-analytics.com
A startup from the ULiège commercializing intelligent software
solutions for active network management and energy systems

8. MISSO
Transmission
network (TN)
DN
DN
DN
MISSO
Transmission
network (TN)
DN
DN
Need for advanced decision-
making strategies
SUPERGRID
Need for MORE-advanced
decision-making strategies
Need for advanced decision-
making strategies

9. Controlling a HVDC supergrid to share
primary frequency reserves

10. From supergrids towards a global grid – a key
infrastructure for a fast energy transition
More at: http://blogs.ulg.ac.be/damien-ernst/tedx-talk-the-global-grid-for-empowering-renewable-energy/

11. Agent
Environment
state
reward
action
numerical value
Reinforcement learning (RL) agent

12. We pioneered the use of these techniques for controlling
power systems and many others followed.

13. Contributions to Reinforcement learning (RL)
Information generalization in
reinforcement learning (fitted Q
iteration, …)
Learning RL policies with
performance guarantees

14. A research interplay,
from electrical engineering
to reinforcement learning
and back.
The Lorentz oscillator illustres admirably well this interaction.

15. To my PhD advisor, my principal referee for this Blondel
Medal, my colleague and my friend, Prof. Louis
Wehenkel : THANK YOU