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.