Master Thesis “representation of Stochastic
Vor 5 Tagen
Master Thesis “Representation of Stochastic Phenomena in Optimizing Energy Management Systems”
Master Thesis “Representation of Stochastic Phenomena in Optimizing Energy Management Systems”
- Center for Energy
- Energy Management Systems (EMS) in the context of local energy communities manage local flexibility such as storage systems and charging stations to support the integration of highly volatile renewable energy sources and loads into the electricity network.
- Several competing methods are available to deal with the highly stochastic phenomena, but no detailed comparison of these methods in the context of EMS in local energy communities is available. The thesis addresses this research gap via a detailed case study evaluating the performance of multiple stochastic and/or robust optimization approaches.
- Throughout this master thesis project, you will work in our multidisciplinary team of technicians, researchers and engineers.
- As part of your master thesis, you conduct a brief literature research in order to identify the most important techniques representing stochastic phenomena in MILP problems.
- Under the guidance of our team you will work on the optimal integration of highly volatile renewable generation and zero-emission mobility loads and will be studying the impact of modeling decisions on the performance of EMS.
- You will also learn how to optimize EMS by formulating Mixed-Integer Linear Programming (MILP) to represent the EMS task.
- Afterwards, will create a simple benchmark system, which will then be used to evaluate the performance of selected modeling techniques.
- Last but not least, a dedicated focus in the evaluation of your results will be put on the accuracy of selected techniques and the risk that some loads cannot be fully supplied.
- You will gain insight into the applied research working environment and will get to explore a cutting-edge research topic.
- You will not only benefit from the scientific support provided by the Electric Energy Systems competence unit, but will also have the chance to interact and share views with experts from other research fields.
Your qualifications as an **Ingenious Partner**:
- Ongoing master’s studies in the field of mathematics, computer science, energy informatics, electrotechnical engineering, physics, industrial automation, or similar
- Solid Python programming and software development skills
- Solid mathematical foundation to efficiently address the questions at hand
- Basic knowledge of stochastic processes and statistics
- Fundamental skills in optimization, first experiences with MILP are beneficial
- Basic knowledge in the field of electric energy systems
- Team player with a curious and determined attitude
- Working proficiency in English or German
**What to expect**:
EUR 1.241;
- gross per month for 30 hours/week based on the collective agreement. There will be additional company benefits. You will be part of our international Young AIT network. As a research institution, we are familiar with the supervision and execution of master theses and we are looking forward to supporting you accordingly.
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Wien, Österreich Austrian Institute of Technology VollzeitAs **Austria's largest research and technology organisation** for applied research, we are dedicated to make substantial contributions to solving the major challenges of our time, climate change and digitisation. To achieve our goals, we rely on our specific research, development and technology competencies, which are the basis of our commitment to...
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