Sustainable Energy Systems Design: Integration of Life Cycle Assessment in Energy Systems Optimization

Institut

Lehrstuhl für Energiesysteme

Typ

Masterarbeit /

Inhalt

theoretisch /  

Beschreibung

Industrial greenhouse gas emissions represent 22 percent of annual global emissions. A speed-up in the transformation of the industrial heating supply is critical to reaching ambitious climate targets. Accurately planning energy supply with a highly spatial and temporal resolution is essential to achieve this acceleration. Linear programming optimization methods are a valuable tool for achieving that. However, these models generally only include economic indicators, producing an environmentally sub-optimal result. Even when sustainability indicators are included, these are generally limited to carbon emissions in the form of a carbon tax.

This master's thesis focuses on integrating the sustainability assessment method of life cycle assessment (LCA) into a linear programming (LP) optimization. The selected tools are all Python-based, open-source: Brightway2 for the LCA formulation, PyPSA for the energy system model and linopy for the custom equations within PyPSA. The new equation system will be implemented for a representative industrial supply case study where several technologies have already been modeled with LCA. A particular focus will be placed on fully reproducible Python code to ensure transparency and replicability of the research process.

Work packages:

1. Literature review
2. Model Formulation
3. Software Implementation with Python
4. Optimization of a case-study

Voraussetzungen

• Fundamental understanding of energy systems and thermodynamics.
• Experience programming with Python or MATLAB.
• Interest in linear programming methods and optimization methods
• Knowledge of life cycle assessment is a plus.

Möglicher Beginn

sofort

Kontakt

Amedeo Ceruti
Raum: 3712
Tel.: +49 89 289 16343
amedeo.cerutitum.de

Ausschreibung