Reinforcement Learning for Battery Dispatch Optimization by Jasper Stolte (Senior AI Researcher - Deep RL)
Join us to explore one of the many applications of reinforcement learning at Shell. In this session, we will delve into how reinforcement learning techniques can optimize home battery charge and discharge management. This project utilizes real-world weather and energy pricing data, combined with a customized algorithm, to create an efficient strategy for managing battery storage in a home microgrid.
Note: after subscribing, showing up is mandatory! There are 100 spots only with first come first serve and only GEWIS members are allowed in. You can earn 1 my future activity with this lecture.
Please contact Corporate Communication and Contact Committee or the board (ceb@gewis.nl) with any questions, concerns or if you are unable to attend after the deadline for unsubscribing has passed. Have fun!
This sign-up list has a limited capacity and is open from Tuesday, April 15, 2025 at 6:00 PM till Monday, April 28, 2025 at 11:59 PM.