Student name: Josien de Koning

Abstract:  Taking into consideration the renewable energy transition and political tensions between regions, it is desirable to become less dependent on fossil fuels. While the Swiss electricity system currently overproduces in summer, it is dependent on imports in winter. This imbalance will continue to increase due to electrification and replacement of nuclear power plants by renewable energy sources such as solar energy. To mitigate this problem, a residential Power-to-Hydrogen-to-Power seasonal energy storage (P2H2P) system is proposed. The system is formulated as MILP energy hub model and optimized towards minimum cost and CO2e-emissions using the Ehub Tool developed at EMPA. While the P2H2P system is technically and spatially feasible, the large size of the pressurized hydrogen tank presents high cost and embodied carbon emissions. As a result, seasonal storage is not part of the optimal solution set both in 2020 and 2040. In order to make the P2H2P system competitive, it is essential to decrease the seasonal storage need by (1) reducing the energy demand in winter, (2) increasing the efficiency of photovoltaics, heat pump and fuel cell and (3) maximizing the PV surface. The P2H2P system shows large cost and carbon intensity improvements between 2020 and 2040. Further research on residential P2H2P systems remains interesting.

Supervisors: Dr. Binod Koirala (Empa), Prof. Dr. Arno Schlüter (ETH Zurich)

📄 Related Publications: How can we save energy for later?

Student name: Jacopo Cipriani

Abstract:  This thesis explores the potential of using gasification to utilize municipal solid waste (MSW) in Switzerland as an alternative to traditional incineration. It compares two methods, oxy-gasification and air-gasification, to see how effectively they can convert waste into valuable energy products such as Hydrogen and Syngas. The thesis concludes that oxy-gasification of MSW can produces high-quality hydrogen and electricity, while air-gasification offers a more practical solution for generating heat and power if the challenges concerning MSW heterogeneity can be overcome.

Supervisors: Dr. Robin Mutschler (Empa), Dr. Eleonora Bargiacchi (ETH Zurich), Prof. Dr. André Bardow (ETH Zurich)

Student name: Alejandro Christlieb Picazo

Abstract:  This project developed a transferable method to assess the climate mitigation potential of nature-based solutions (NBS), using green roofs in Zurich as a case study. A spatial multi-criteria decision analysis (MCDA) was combined with high-resolution emissions modeling to identify effective NBS allocation. Results showed that green roofs reduced heating emissions by 0.6–3.3%, depending on adoption rates. The approach built on existing tools and included stakeholder input, offering a replicable framework to support the integration of NBS in urban decarbonization and resilience strategies.

Supervisors: Dr. Mashael Yazdanie (Empa), Prof. Dr. Russell McKenna (ETH Zurich)

Student name: Madeleine Kyne

Abstract:  This project assessed the resilience of Accra, Ghana’s energy system to flood-induced substation outages using an energy system optimization model (ESOM). The analysis compared system designs under different Shared Socioeconomic Pathways (SSPs), with and without accounting for outage risks. Substation outages were modeled as production constraints, and system cost and unmet demand were used to evaluate resilience. Designs that considered outages outperformed those that did not, especially under high-demand, high-emissions scenarios. Outage-aware strategies increased investment in distributed, off-grid technologies, improving system resilience. The study provided a replicable framework for outage analysis in data-scarce regions and highlighted trade-offs in energy system planning under extreme weather risk.

Supervisors: Dr. Mashael Yazdanie (Empa), Prof. Dr. Gabriela Hug (ETH Zurich)

Student name: Roxanne Vanderberghe

Abstract:  As society moves toward net-zero emissions, hydrogen is gaining attention as a clean energy carrier. However, electrolysis-based hydrogen production still struggles to compete economically with natural gas reforming and coal gasification. This thesis addresses that challenge by developing a mixed-integer linear programming model to minimize the cost of a hydrogen generation site through optimal component sizing and operation. A key innovation lies in recovering waste heat from electrolysers and exporting it to a high-temperature district heating network. This approach, combined with integrated system optimization, reduces the value-adjusted levelized cost of hydrogen (VALCOH) by 18.9%. The model also features detailed cost and operation representations, especially for the electrolyser. Modeling electrolyser efficiency using a piecewise affine approximation with more breakpoints further reduces VALCOH by 3.9%.A comprehensive sensitivity analysis highlights electricity prices and electrolyser efficiency as the most influential factors. In summary, this work demonstrates the value of combining waste heat recovery, accurate efficiency modeling, and joint sizing-operation optimization to enhance the cost competitiveness of electrolysis-based hydrogen production in multi-energy systems.

Supervisors: Dr. Gabriele Humbert (Empa), Dr Hanmin Cai (Empa), Dr. Binod Koirala (Empa) and Prof. Dr. Giovanni Sansavini (ETH Zurich)

📄 Related Publications: Vandenberghe, R., Humbert, G., Cai, H., Koirala, B. P., Sansavini, G., & Heer, P. (2025). Optimal sizing and operation of hydrogen generation sites accounting for waste heat recovery.  Applied Energy, 380, 125004.

Student name: Mathias Giesbrecht

Abstract:  This thesis examines the feasibility of creating a Hydrogen Valley in Switzerland’s Rheintal region, where hydrogen could play a key role in the transition to clean energy. The study finds that Sustainable Aviation Fuel (SAF) production in the region could be economically viable at a tipping point around 2 CHF/L of fuel. Therefore, this thesis provides valuable insights into how hydrogen and CO2 could be used in regional energy systems to support Switzerland’s climate goals and the supply of SAF.

Supervisors: Dr. Robin Mutschler (Empa), Arijit Alip Upadhyay (Empa, ETH Zurich), Dr. Gianfranco Guidati (ETH Zurich), Prof. Dr. André Bardow (ETH Zurich)

Student name: Mathias Giesbrecht

Abstract:  This thesis focuses on the concept of energy self-sufficiency, or “autarky,” and how it can be applied to the Swiss energy system. The study develops new methods to quantify how much of a region’s energy needs can be met through local production. The findings show that energy autarky can be quantified accurately and efficiently, helping policymakers understand the economic and environmental benefits of self-sufficient energy systems. The research provides practical tools for creating more resilient and sustainable energy systems in Switzerland, helping to reduce reliance on external energy sources.

Supervisors: Dr. Robin Mutschler (Empa), Dr. Dennis Beermann (Empa), Prof. Dr. Giovanni Sansavini (ETH Zurich)

Student name: Andrea Gattiglio

Abstract: Demand side management is perceived as a tool to support a secure and reliable energy system operation amid the growing integration of renewable energy resources. However, the lack of scalable modeling and control procedures hinders the practical implementation. To address this challenge, this thesis focuses on a novel signal matrix model predictive control algorithm. Compared to existing data-driven methods, this approach explicitly provides stochastic predictions considering both disturbance and measurement errors with few tuning parameters, ensuring reliability by high-probability constraint satisfaction. The performance is extensively compared with three state-of-the-art algorithms in a space heating case study using a high-fidelity simulator.

Supervisors: Dr. Hanmin Cai (Empa), Prof. Dr. Roy Smith (ETH Zurich)

📄 Related Publications: Yin, M., Cai, H., Gattiglio, A., Khayatian, F., Smith, R. S., & Heer, P. (2024). Data-driven predictive control for demand side management: Theoretical and experimental results. Applied Energy, 353, 122101.