Lectures and Courses
The Chair for Energy Systems Analysis offers the following lectures and courses:
If you are interested in working on a Bachelor, Semester, or Master project with us, you can find the projects we currently offer below or on external page SIROP. For further information, visit our student projects page for more insight into previous student work done with the Chair.
In case you have project ideas not currently related to any of these projects, please feel free to propose your own project and send your ideas to .
Life Cycle Analysis (LCA) of an AI system used in the energy sector
While artificial intelligence (AI) increasingly contributes to the digitalization of energy systems, there is a growing interest in assessing AI’s environmental implications. AI systems that for example perform forecasts of photovoltaic (PV) plants or electricity consumption can improve system operation, reduce curtailment, and enhance system reliability. However, these systems themselves consume computational resources, labour and materials and thus create environmental impacts. A Life Cycle Analysis (LCA) can help quantify the sustainability of AI systems and shed some light into the net-benefits they offer to the energy systems.
Keywords
Artificial intelligence, energy systems, life cycle analysis (LCA), policymaking
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Master Thesis
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Published since: 2025-07-09 , Earliest start: 2025-07-08
Organization Chair of Energy Systems Analysis
Hosts McKenna Russell , Heymann Fabian
Topics Engineering and Technology
Forecasting Data Centre Diffusion and Energy System Impacts
The use and exchange of data is exponentially growing with ongoing digitalization across all economic sectors and societal activities. This trend is paralleled by the expansion of digital infrastructures, such as data centers (DC). The locations of DC are so far remarkably clustered, yet the locational factors that influence DC siting are not well understood. Hence, there is a need for comprehensive methodologies to analyse why DCs are located and to predict where and when future DCs might appear. From the energy system side, such forecasts can become the basis for impact assessments to robustly analyse potentials and risks the adoption of DCs could pose to local energy system systems.
Keywords
Data centers, Energy systems, Digitalization, Forecasting, Geographic information systems
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Master Thesis
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Published since: 2025-07-09 , Earliest start: 2025-07-07
Organization Chair of Energy Systems Analysis
Hosts McKenna Russell , Heymann Fabian
Topics Engineering and Technology
Accelerating the Energy Transition with Artificial Intelligence
The global energy transition requires robust planning and detail-rich decision-making tools to address the increasing complexity of decarbonizing and digitalizing energy systems. As the urgency of the climate crisis intensifies, artificial intelligence (AI) has emerged as a potentially transformative technology for accelerating the energy transition. Despite growing interest, AI's integration into established energy system models and planning processes remains yet fragmented and underexplored. In Switzerland, the Swiss TIMES energy system model (STEM) serves as a central reference for evaluating national pathways toward net-zero emissions. In the part of this master thesis, the applicant would be developing a comprehensive framework to study techno-economic effects of digital technologies such AI on energy systems. In the next step, the framework will be integrated into STEM in order to identify and study the effects of AI on energy system transitions in unprecedented detail.
Keywords
Artificial intelligence, Energy systems, Impact assessment, Energy policy
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Master Thesis
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Published since: 2025-07-09 , Earliest start: 2025-07-07
Organization Chair of Energy Systems Analysis
Hosts McKenna Russell , Heymann Fabian
Topics Engineering and Technology
Developing an interactive dashboard for decarbonization strategies in Switzerland
In 2019, the Swiss Federal Council adopted a long-term climate strategy committing to net-zero greenhouse gas emissions by 2050, whereby anthropogenic emissions must be fully offset by removals through natural carbon sinks and engineered sequestration technologies. In alignment with this objective, the project Swiss Center of Excellence on Net Zero Emissions (SCENE) was established to advance research and innovation in support of the 2050 net-zero target. SCENE represents a strategic collaboration among six Swiss research institutions — ETH Zurich, EPFL, the Paul Scherrer Institute (PSI), the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Empa, and Eawag—each contributing with domain-specific expertise. Apart from a significant scientific advancement, one of the important missions of the SCENE project is communicating its results to the public.
Keywords
Energy system transition, Data visualisation, Sustainability, Power BI
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Semester Project
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Published since: 2025-07-09 , Earliest start: 2025-07-04
Organization Chair of Energy Systems Analysis
Hosts Lohrmann Alena , McKenna Russell
Topics Engineering and Technology
Balancing trade-offs between resource availability, landscape quality, property price and visual impact in feasibility assessment of wind farm development
Transitioning from fossil fuels to renewable energy sources (RE) is crucial for mitigating climate change and ensuring a sustainable future. Usually, the feasibility of the energy transition on the local scale is assessed by considering the technical and economic potentials of RE technologies, as well as their environmental impact. However, the plans for the energy system transition often encounter local opposition. Communities near proposed wind farms may express concerns about their visual impact, noise, or changes to their way of life. In this regard, identifying and understanding the trade-offs between different factors that may influence the local development of wind technologies is a nontrivial task.
Keywords
GIS analysis, machine learning, renewable energy
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Semester Project , Master Thesis
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Published since: 2025-06-17 , Earliest start: 2024-08-19
Organization Chair of Energy Systems Analysis
Hosts Lohrmann Alena , McKenna Russell , Chen Ruihong
Topics Engineering and Technology
Design and optimal sizing of renewable energy-powered water microgrids
Recently, microgrids have been recognized as a promising solution to tackle the rising number of power outages caused by extreme weather events affecting our cities and communities. These conditions, frequently induced by climate change, result in effects that go beyond damage to the energy infrastructure. The water systems are equally vulnerable to extreme weather events (including droughts caused by heat waves and floods), affecting the supply of clean water, the treatment of wastewater, and the management of stormwater. Recognizing the similarity of electricity and water microgrids, the project proposes to create a unified framework for renewable energy-powered water microgrids using concepts from electricity microgrids.
Keywords
Modelling, water supply, water and energy security
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Master Thesis
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Published since: 2025-06-17 , Earliest start: 2024-08-19
Organization Chair of Energy Systems Analysis
Hosts McKenna Russell , Lohrmann Alena
Topics Engineering and Technology
Multi-criteria decision analysis (MCDA) of wind deployment in Europe considering different system impacts
The deployment of onshore wind energy across Europe is influenced by multiple factors, including technical constraints, economic feasibility, environmental sustainability, and social acceptance. While cost-optimal solutions are commonly pursued, a more nuanced approach that considers trade-offs between various objectives is essential for informed decision-making. Different objectives such as low visual landscape disturbance, high monetary benefits, low annoyance to low residents, good wildlife protection etc., are summarized in a systematic review. To explore the trade-offs among these objectives from different stakeholders’ perspectives, Multi-criteria Decision Analysis (MCDA) is necessary for evaluating different possible alternatives.
Keywords
Renewable, energy, modelling, GIS, MCDA, scenario analysis
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Master Thesis
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Published since: 2025-06-17
Organization Chair of Energy Systems Analysis
Hosts Lohrmann Alena , McKenna Russell
Topics Engineering and Technology
Evaluating water extraction from solid sorbent direct air capture for low-carbon fuel production
Phasing out fossil fuel-based economies is a tremendous challenge in the effort to meet the 2°C climate target. First, low-carbon energy systems, fuels, and technologies must be fully integrated into the global energy system to achieve required greenhouse gas (GHG) emission reductions. Second, unavoidable GHG emissions must be removed from the atmosphere with carbon dioxide removal (CDR) technologies to achieve net-zero CO2 and GHG emissions in the 21st century. A portfolio of CDR technologies has been proposed, both nature- and technology-based CDR options. Direct air capture (DAC) with CO2 storage is a technology-based solution and is among the CDR technologies with the highest future CDR potential, up to 40 GtCO2/year. Alternatively, the CO2 sourced from DAC can produce low-carbon fuels instead of being stored permanently in geographical layers. Low-temperature DAC typically uses a sorbent to capture CO2 from the ambient air, which is challenging due to the highly dilute concentration of CO2 in ambient air requiring considerable energy requirements for CO2 capture. Latter energy requirements and the generation of by-products (such as water) are highly influenced by ambient air conditions, for example, relative humidity and temperature. Water is becoming an increasingly scarce resource, yet it is essential for producing many forms of energy (including low-carbon fuels, which are needed to tackle climate change). This dependency is known as the water-energy nexus and is a growing concern among many researchers. Previous studies have mainly focused on the costs and life cycle GHG emissions of DAC. However, one of the neglected aspects of solid sorbent DAC is the generation of pure water as a by-product. In this context, water produced via the DAC process could potentially be used to produce low-carbon fuels (e.g., methanol, synfuels, etc.) by combining captured atmospheric CO2 (from DAC), water, and other feedstocks.
Keywords
Direct air capture, water footprint, e-fuels, sustainability, GIS analysis, Energy systems
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Master Thesis
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Published since: 2025-06-17
Organization Chair of Energy Systems Analysis
Hosts McKenna Russell , Lohrmann Alena , Terlouw Tom
Topics Engineering and Technology