Timothée Hornek received his Master’s degree in Simulation Technology from the University of Stuttgart (Germany), in 2022. His research interests are in computer science and optimization, focusing on machine learning and energy systems. During his bachelor’s thesis, he studied nonlinear phenomena in energy storage systems. Throughout his master’s degree he turned his focus to computer science-related subjects and projects. Notably, he explored the possibility to use tensor frameworks to implement the sparse grid approximation method and to solve partial differential equations using the latter. During his master’s thesis, he developed a genetic algorithm to approximate the solution of a novel assembly line balancing problem.
After graduation, he joined the FINATRAX research group, where he works on a project in cooperation with Enovos, which is Luxembourg’s main energy supplier. His research focus is on short-term electricity price forecasting in the German intraday electricity market. In particular, he applies ML and AI methods to study price fluctuations in the context of a wide variety of possible influencing factors. For instance, imbalance markets, load forecasts, and renewable energy generation forecasts are considered. He aims to apply the insights on price influencing factors to develop more accurate probabilistic price prediction models, which can be used to improve trading strategies in the continuous intraday market.