Thesis: Multi objective dynamic operation of a continuous oscillatory baffled zeolite synthesis reactor using uncertain day-ahead predictions
- Thesis offer
The electrification of the energy supply requires major changes in the process industry, which brings new challenges and opportunities for process operation. Especially, the usage of renewable electric energy sources is a main challenge due to the highly volatility of production and price.
The hydrothermal synthesis of zeolites requires long processing times at elevated temperatures, which poses a challenge for the economical and ecological efficient operation at fluctuating energy supplies. The usage of model-based optimization techniques circumvent this problem and enables a flexible energy price based zeolite production.
When optimizing the future operation the energy price is still unknown. Therefore, there exist several energy price prediction models. However, forecast and the energy price differ. The objective of this work is to quantify these differences and include the prediction uncertainty in the optimization
Objectives of the Master Thesis
- Literature research to the topics:
- Osillatory baffled reactor
- Zeolite synthesis
- Electrified energy
- Energy price forecasting
- Multi objetive optimization
- Performance measure of Energy price forecasting model
- Implementation and testing of multi objective optimization in an existing dynamic optimization framework (python)
Prerequisites
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Basic programmic skills
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Interest and motivation on theoretical work.
Other
- Start as soon as possible
- Duration of 6 month (Master's thesis)
- Advantages: You will get a free cookie