Master Thesis: Development of a Modular Python-Based Tool for Techno-Economic Screening of District Heating Modernisation and Renewable Energy Source Integration Scenarios

AEE INTEC

AEE – Institute for Sustainable Technologies (AEE INTEC) is a non-university research institute founded in 1988. AEE INTEC currently employs around 90 people from more than fifteen nations and continuously awards dissertations, master’s theses and internships. AEE INTEC works in the fields of „Buildings“, „Cities and Networks“, „Technology Development“ and „Industrial Systems“ on fundamental and application-oriented research in national and international R&D projects in cooperation with universities, colleges, other research institutions and industry.

Research Project

This Master’s thesis will be embedded in the ENABLE DHC project, which supports frontrunner cities and regions across Europe in the transition of their local and District Heating and Cooling (DHC) systems toward greater sustainability and climate neutrality. A particular focus is placed on Task T3.1 – Strategic Investment Planning, which aims to support investment prioritization by municipalities and operators through tools, methods, and participatory processes.

One of the needs identified within this task is the development of a user-friendly, modular tool that supports early-stage techno-economic assessment of DH modernization options. These include integration of renewable energy sources, decentralized supply units, and system-level interventions such as reducing supply temperatures or extending networks.

Outline of the Bachelor Thesis

The Master’s thesis will focus on the development of a Python-based application that allows users (e.g., planners, municipalities, utility partners) to assess multiple modernization scenarios as a support for strategic-level decisions in early project phases.

The core features of the tool will include:

• A scenario input interface for key parameters (e.g., energy source mix, cost assumptions, network interventions),
• A calculation module for estimating CAPEX/OPEX and basic energy flows,
• A modular architecture that enables easy adaptation for different city contexts or use cases,
• A multi-criteria evaluation logic, possibly including stakeholder-adjustable weights,
• Optionally, exportable results or visualization capabilities for investment discussions.

The development will rely on open-source Python libraries (e.g., Pandas, Plotly) and will be aligned with the needs of case study partners in the ENABLE DHC project.

We expect…

• Interest in sustainable energy planning and urban infrastructure
• Good programming skills in Python
• Educational background in mechanical engineering, energy engineering, or a closely related technical discipline

We offer…

• Paid Master’s thesis, embedded in a current European research project
• Intensive support from experienced researchers in the field of thermal energy technologies
• Planned duration: 6 months, Start: from now on, Place of realization: Gleisdorf, Austria

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