Opportunities

This project aims to assess the systemic relevance of Swiss DSOs for security of electricity supply by leveraging geodata and multi-criteria analysis. The research will involve the following steps: • Data collection and integration: Geospatial data on various energy data using Geographic Information System (GIS) tools (also available as Python or R packages). • Systemic relevance analysis: A scoring framework will be developed to quantify the systemic relevance of each DSO. Indicators will be weighted based on their importance to security of supply, using statistical methods and expert input. • Visualization and validation: Geographic Information Systems (GIS) will be used to create maps showing the systemic relevance of Swiss DSOs will results will be validated with domain experts.

The outcomes will include a ranked assessment of DSOs based on their systemic relevance and visualizations that highlight the criticality over the Swiss terrain, to strengthen Switzerland’s energy security.

If you are interested in the project, please forward your CV and transcript by e-mail to Dr. Fabian Heymann fheymann@ethz.ch

This project aims to develop a methodology for analysing and comparing global energy systems using key indicators, including the share of renewable electricity generation, electrification rate, and system reliability. The research project will follow a three-phase approach: 1. Data collection and preprocessing: Aggregating publicly available datasets from sources such as the International Energy Agency (IEA), World Bank, and national energy reports. 2. Explorative data analysis: Employing statistical and machine learning methods to assess the interrelatedness of each indicator and deriving similar energy transition groups. 3. Clustering and validation: Applying clustering techniques such as k-means or hierarchical clustering to identify distinct groups of energy systems. Results will be validated against external benchmarks and case studies to ensure robustness.

The outcomes will include a typology of global energy systems as well as the visualizations of clusters, and deducing first, high-level policy recommendations tailored to the unique characteristics of each energy system.

If you are interested in the project, please forward your CV and transcript by e-mail to Dr. Fabian Heymann fheymann@ethz.ch

TASK DESCRIPTION • Mathematical Modeling: Understand and accurately implement the mathematical models underlying MCDA methods. • Tool Development: Design and develop the MCDA online tool using Python, implementing multiple MCDA methods for preference elicitation. • Data Visualization: Create interactive data visualizations using libraries such as D3.js or Pythonbased tools to effectively present analysis results. • User Interface Design: Develop a user-friendly interface that allows for easy input of data and interpretation of results. • Testing and Validation: Perform thorough testing to ensure the tool's functionality, reliability, and accuracy. • Documentation: Document the development process and prepare user manuals or guides.

We are offering an exciting internship opportunity for a motivated Master's student to contribute to the development of an online tool designed for eliciting user preferences using various MCDA methods. The tool will be programmed in Python and will feature interactive data visualization components to enhance user engagement and comprehension.

Dr. River Huang (river.huang@psi.ch)

The Swiss Energy Strategy 2050 aims to achieve zero net emissions target as of 2050. The four leading Swiss research institutes — Paul Scherrer Institute (PSI), Swiss Federal Laboratories for Materials Science and Technology (EMPA), Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), and Swiss Federal Institute of Aquatic Science and Technology (EAWAG)—are at the forefront of this en-deavour. In the context of the SCENE project, these institutes are collaboratively developing science-based roadmaps that outline the anticipated pathways to attain net-zero emissions before 2040. The tran-sition to net zero requires a multifaceted approach, encompassing technological advancements, con-sumption reductions, and market-based mechanisms for emission compensation and reduction. An es-sential component of this transition is a comprehensive CO2 emission-related cost analysis. This analysis will evaluate the financial implications of shifting energy technologies, reducing consumption, and imple-menting market-based emission compensation and reduction strategies.

The goal of this project is to build on existing work to assess the costs and emissions reduction poten-tials of individual measures at the four RIs. These measures need to be assessed both individually and collectively in the context of a Marginal Abatement Cost Curve. The results will be used to elaborate a Roadmap for each of the institutions, in order to outline a realistic pathway to achieve net zero by 2050. Steps in this project include: • Estimating the costs of emission reduction strategies of waste, paper and water management for four research institutes • Exploring the feasibility and accessing the costs of biomass heating technologies combined with biochar for four research institutes (can be a generally small utility) • Developing a potential small-scale optimization model that covers various technologies to design long-term net-zero roadmaps for four institutes (existed data can be used) • Life cycle assessment of energy efficiency improvement measures/projects such as virtual meet-ing emissions • Visualization of emission reduction pathways and cost implications using interactive/online tools

See above or attached