Theoretical difficulty: Mid Practical difficulty: High
Abstract
The aim of this Thesis is to predict the electricity price for the Hydrogen plants from open-sourced Energy data provided by the European Network of Transmission System Operators (ENTSO-E) [1]. We explore multiple machine learning techniques to achieve this aim. At the end, a standalone GUI is provided, that can be used in the industry with ease. This work was done in collaboration HyCenta Research GmbH.
Further, this thesis seeks to address the following research questions:
How do different determinants such as the electricity mix (the proportion of energy from various generation sources), in-house generation, and gas prices, influence the cost of electricity?
Which machine learning approaches/algorithms are most suitable for accurately predicting future electricity price trends, particularly in Austria or other European countries?
To what extent does the sensitivity of our model to inputs, like solar and wind energy, affect its overall accuracy and reliability in predicting electricity prices?
Internship Student at the Montanuniversität Leoben
Short bio: Etienne KPANOU is a Master student in Complex Systems Engineering with a specialization in Aeronautics-Space and Automotive Mechatronics at the University of Technical Sciences of Bordeaux and has been interning since July 2023 at the Chair of Cyber-Physical Systems at the Montanuniversität Leoben.
Research Interests
Research and innovation in robotics
Aeronautics-space and Automotive
Thesis
Teleoperation of mobile robot based on vision and human finger (Ongoing)
Master Thesis Student at the Montanuniversität Leoben
Short bio: Klemens is an Energy Engineering student at Montanuniversität Leoben, working on a Master’s Thesis named “Deep Neural Energy Forecasting for Economic Resource Usage in Hydrogen Industries”. This work focuses on exploring how AI can be used to better manage resources in the hydrogen industry.
Klemens got his start in Electrical Engineering, graduating from a technical secondary school. After a brief but interesting stint with the Military Orchestra in Carinthia, he decided to return to his engineering roots, earning a Bachelor of Science in Raw Materials Engineering.
Now, as a Master’s candidate, Klemens hopes to combine his skills and interests to make a positive contribution to the energy sector.
Klemens Lechner, B. Sc Master Thesis Student at the Chair of Cyber-Physical-Systems Montanuniversität Leoben Franz-Josef-Straße 18, 8700 Leoben, Austria
Benjamin Schoedinger, B.Sc Master Thesis Student at the Chair of Cyber-Physical-Systems Montanuniversität Leoben Franz-Josef-Straße 18, 8700 Leoben, Austria
Bachelor Thesis Student at the Montanuniversität Leoben
Short bio:
Christoph is a bachelor student in Mechanical Engineering at Montanuniversität Leoben. His fascination for industrial robotics and automation already started at high school, where he worked on a collaborative robotics project during his final thesis.
In June 2023, he finished his bachelor’s thesis at CPS.
Christoph Andres, B.Sc. Bachelor Thesis Student at the Chair of Cyber-Physical-Systems Montanuniversität Leoben Franz-Josef-Straße 18, 8700 Leoben, Austria
Short bio: Iye Szin Ang join the CPS team in Nov. 2023 as doctoral student. Before that she completed her Master thesis at the chair within the Erasmus Mundus Joint Master Degree in Photonics for Security Reliability and Safety (PSRS). Her thesis topic was on human-robot interaction using sign language.
Continuing her prior work, she aims in her doctoral study at creating a natural and intuitive way for humans to communicate with machines. This approach will not only make robots more inclusive and accessible, but also provide a non-verbal and non-intrusive way for people to control and communicate with them. With a passion for advancing the field of CPS through cutting-edge research and innovation, Iye Szin is dedicated to creating more meaningful and inclusive technology for everyone.
Master Thesis Student at the Montanuniversität Leoben
Short bio: Christopher is a master student in Industrial Engineering with a specialization in Data Science at the Polytechnic University of Catalunya (UPC BarcelonaTech) and, as of September 2023, finished his master thesis at the Chair of Cyber-Physical Systems in Montanuniversität Leoben.
Graduated in June 2020 from his Bachelor studies in Electronics Engineering from Tecnocampus Mataro (UPF) where he was a member of the Bytemaster Tecnocampus Racing Team, which participated in the 6th edition of the Motostudent competition. Furthermore, he is a current member of the Montan Factory Racing team in Montanuniversität Leoben, which will be participating in the 7th edition of the Motostudent competition in October 2023.
Research Interests
Bayesian optimization
Cyber-physical systems applied to Motorsports Mechatronic systems Digital twins
Christopher Martin Shimmin, M. Sc. Master Thesis Student at the Chair of Cyber-Physical-Systems Montanuniversität Leoben Franz-Josef-Straße 18, 8700 Leoben, Austria
Bachelor Thesis Student at the Montanuniversität Leoben
Short bio: After starting his education in the field of mechanical engineering, Marco followed his growing passion domain of computer science, especially focusing on machine learning.
Currently, he is finishing his bachelor’s degree in Industrial Data Science at the Montanuniverstät Leoben. Since 2021 he is working at the Department of Information Technology. Additionally, since 2022 Marco works as a software developer at voestalpine Wire Austria GmbH.
In his thesis, he is developing a program to simplify the interaction between the ROS2 and the ESP32 microcontroller.
Research Interests
Robotics
Thesis
Contact
Marco Schwarz Bachelor Thesis Student at the Chair of Cyber-Physical-Systems Montanuniversität Leoben Franz-Josef-Straße 18, 8700 Leoben, Austria