Wind Farm Dynamic Yield Optimization using Reinforcement Learning

16:43-16:55, January 27 @ 2BC

Talk/ Overview

We present an application of Reinforcement Learning to dynamically optimize the energy yield of a wind farm. The developed algorithm minimizes, autonomously and in a data-driven way, negative aerodynamic interactions between wind turbines, and determines their optimal operational settings.

Talk/ Speakers

Giorgio Cortiana

Head of Advanced Analytics, E.ON Digital Technology

Talk/ Slides

Download the slides for this talk.Download ( PDF, 10271.9 MB)

Talk/ Highlights

13:02

Wind Farm Dynamic Yield Optimization using Reinforcement Learning

With Giorgio CortianaPublished March 12, 2020

AMLD / Global partners