Explore the 2025 Challenges

We have compiled a selection of urgent and concrete real-world challenges that our Industry and Public Sector Partners are currently facing. For more details, please see the Download challenge presentations (PDF, 15.5 MB) from the Kickoff.

Partner: Axpo

Contacts: Paul Letainturier, Antonia Graf, David Bugmann

General Description and Problem Formulation

Axpo is the largest electricity producer in Switzerland and a leading company in renewables and energy trading across Europe. In our mission to contribute to a Swiss secured and decarbonized electricity supply, we are focussing our efforts on deploying wind parks in Switzerland. We already count several projects in the pre-construction phasesacross the whole country.

A key challenge in developing wind parks in Switzerland is assessing the feasibility and costs of connecting them to the electrical grid. Traditionally, project developers must identify which grid operators own the surrounding grids and evaluate several connection options through multiple iterations with them.

How can innovative, data-centric approaches (satellite-imagery processing, automated requests, standardized cost assessments, etc.) help reduce the time and uncertainty involved in this process? Through this challenge, we would like to develop a prototype tool with you that automates as many tasks as possible for grid connection assessment.

To support the challenge, we will provide you with a real-world case study of a potential wind farm project in Switzerland. This prototype could then be extended to other assets on the Swiss grid (datacenters, solar parks, EV charging stations, etc.).

Research Questions

How can the grid connection assessment process for wind parks be sub-divided into standard tasks?
Which tasks can be fully or partially automated, based on which tools?
How much time and money could be saved thanks to the partial automation of this process?
What are the challenges faced when utilizing such tools?

Deliverables

Minimal Viable Product in the form of a software prototype applied to wind park projects in early development phases in Switzerland – including user notice
Associated report describing the project, the main challenges, the potential of such automation tools and the next steps for full-scale deployment and duplication to other technologies (datacenters, solar, EV charging)

Expertise Required

Good understanding of electrical grids and power generation technologies
Good understanding of Civil Engineering for grid construction
Data Engineering and coding skills

References

Axpo, external page “Wind Energy in Switzerland: its role and potential”, white paper, 2025
UVEK, external page Interactive mapping of Wind installations in Switzerland, 2025
ETHZ, “Where should wind turbines be constructed in Switzerland?”, 2023

Partner: BKW, Swissgrid

Contacts: Jill Huber, André Semadeni, Gudrun Hoeskuldsdottir, Jared Garrison

General Description and Problem Formulation

Switzerland is rapidly increasing its share of renewable electricity, with photovoltaics leading the way. Solar generation doubled over the past three years, adding nearly 6 TWh to the country’s total generation by 2024. While this development accelerates the urgent decarbonization of the energy sector, it also creates new challenges for grid stability and balancing. To handle greater energy supply volatility, a range of technologies are increasingly required to provide flexibility services and ensure stable grid operation.

Today, much of this flexibility in Switzerland is provided by pumped hydropower storage reserves. However, these reserves often run low in late winter and spring, and the potential to expand capacity further is limited. In recent years, Switzerland has therefore drawn on emergency diesel generators, made investments in gas-fired plants, and seen an expansion of battery installations to provide flexibility. While technically effective, these solutions are often either emission-intensive or carry a high-impact materials footprint.

This raises a critical paradox: Does pushing renewables inadvertently lead to balancing solutions that are themselves environmentally unsustainable? Could there be more sustainable, low-carbon alternatives to provide the same grid services?

Our challenge invites you to critically evaluate and compare the sustainability of different flexibility technologies and to consider alternative flexibility portfolios that can ensure grid stability while minimizing the environmental footprint of Switzerland’s energy transition.

Research Questions

How can the environmental performance—with a particular focus on lifetime greenhouse gas emissions (in CO2e) and material impact—of different flexibility technologies be assessed in a standardized way that enables meaningful comparison across options?
How environmentally sustainable are today’s balancing solutions (e.g. hydropower, batteries, diesel gensets, gas plants) used in Switzerland and neighbouring countries, with a particular focus on lifetime greenhouse gas emissions (in CO2e) and material impact?
Which alternative technologies are expected to or could (also consider less-explored solutions) provide more environmentally sustainable flexibility (e.g., demand-side flexibility, thermal storage, hydrogen, vehicle-to-grid, advanced hydropower optimization)?
How suitable are those alternatives for different balancing services such as aFRR, mFRR, and congestion management?
Based on your findings from research questions 1-4, how could a more sustainable, reliable, and scalable flexibility portfolio for Switzerland’s grid balancing look like, compared to current developments and strategies?

Deliverables

A comparative assessment of past, current, and possible future flexibility technologies in Switzerland and other EU countries regarding lifetime emission intensity (e. g. CO2e/MWh), material-impact, and technical performance.
A technology matrix mapping different flexibility technologies to balancing services (aFRR, mFRR, congestion management).
Scenario analysis that proposes sustainable flexibility portfolios and evaluates their environmental benefits compared to today’s reliance on hydro/diesel/gas/batteries, based on yearly production and flexibility activation profiles.
A final report and presentation, including a detailed explanation of the methodology used to assess environmental performance, along clear data visualizations, scenario results, and actionable recommendations.

Expertise Required

Technical: Knowledge of grid services, balancing mechanisms, and flexibility technologies
Analytical: Life-cycle emissions, sustainability assessment, and quantitative reasoning.
Economic/Policy: Familiarity with energy markets, sustainability frameworks, and regulatory aspeccts
Programming/Data Science (optional): Simulation of balancing profiles, dispatch models, greenhouse gas outcomes
Communication: Ability to present findings in a clear, concise, and impactful way

References

ETH Zurich’s “Flexibility and sector coupling in energy systems: definitions and metrics” – a robust Swiss-led study on flexibility frameworks Research Collection
EU Parliament (2025) report “Increasing Flexibility in the EU Energy System”, exploring flexibility needs and options across timeframes external page European Parliament
CERRE (2025) report “Flexibility in the Energy Sector”, detailing flexibility mechanisms, market/regulatory enablers, and technology contributions external page CERRE
Nature Communications Earth & Environment (2023) article “Energy system transformation pathways to net-zero in Switzerland”, contextualizing Swiss system transformation external page Nature
Life-cycle assessment studies: e.g., cradle-to-grave analysis of industrial lead-acid batteries external page RSC Publishing, LCA of large-scale lithium-ion battery storage external page Syddansk Universitet, and LCA of diesel generator emissions external page ResearchGate
ecoinvent database for emission factors (license needed)
The SFOE’s external page energy statistics for Switzerland

Partner: GE Vernova

Contacts: Gian-Luigi Agostinelli

General Description and Problem Formulation

In the race to decarbonize power generation, hydrogen via electrolysis and CO₂ capture technologies dominate the spotlight. By contrast, direct methane splitting (CH₄ → H₂ + C) has received less attention, partly because of the apparent loss in fuel heating value. Yet methane remains abundant, and global infrastructure for its transport is already in place.

If efficient and scalable, methane splitting could provide low-carbon hydrogen while producing solid carbon as a potentially valuable by-product (e.g., in construction materials, batteries, or agriculture). The question is: what would it take for this pathway to become competitive? Students will be asked to explore technical, economic, and application-driven requirements that could make methane splitting a realistic alternative in the decarbonization toolbox.

Research Questions

What cost, efficiency, and scalability targets are required for CH₄ splitting technologies to compete with electrolysis or CCS pathways?
How should operational features such as start-up time, flexibility, and safety be prioritized for central vs. distributed power generation applications?
What realistic market opportunities exist for the carbon by-product, and could carbon rather than hydrogen become the primary revenue driver?
What lessons can be learned from past or ongoing technology developments in this field?

Deliverables

A literature and patent/IP overview on methane splitting technologies.
Assessment of current R&D status, key players, and failed approaches (with lessons learned).
Identification of major technical and economic challenges, with proposed Key Performance Indicators (KPIs) for success.
Structured recommendation on viability and potential business models.

Expertise Required

Technical and economic assessment.
Critical analysis of technology readiness and application fit.
Ability to synthesize problem statements into actionable KPIs.

Partner: Huawei Technologies Switzerland

Contacts: Dr. Paolo Gabrielli, Eric Aschari

General Description and Problem Formulation

Virtual power plants (VPPs) are a recent energy paradigm that integrates different decentralized energy sources, such as solar panels and battery energy storage systems (BESS), into a unified platform. Via advanced energy management techniques and data analytics, VPPs enable efficient energy distribution and trading, contributing to a more efficient and sustainable energy system¹.

Within this context, energy storage allows to compensate the mismatch between renewable energy generation and energy demand, as well as to perform arbitrage on wholesale electricity markets. Additionally, energy storage is increasingly being used to provide ancillary services to electricity grids, such as frequency regulation and voltage support to maintain stable and efficient grid operation. The combined provision of all such services is key to improve the profitability of energy storage systems and foster their deployment ^2,3.

This project focuses on the role of BESS to produce value for the VPP stakeholders, namely: (1) the final end-users, who might install BESS coupled with solar photovoltaic (PV) to increase self-consumption, reduce energy costs, and obtain remuneration via market participation through VPPs, and (2) the VPP aggregator, who aim at maximizing their profit by providing multiple services to the electricity grid and participating in multiple energy markets with aggregated resources.

Research Questions

Consider an aggregated BESS capacity operated in a VPP to provide both behind-the-meter (BTM) services, e.g., peak-shaving and maximum self-consumption, and front-of-the-meter (FTM) services, e.g., simultaneous participation in wholesale and frequency regulation markets. The specific BESS application and case study, as well as the specific BTM and FTM applications to be considered, will be defined together with the students. Formulate an optimization and assessment algorithm to address the following research questions:

What is the optimal operation of an aggregated BESS for maximizing VPP profitability and minimizing the energy costs of end-users?
What is the impact of BESS technical constraints and BESS degradation on the optimal BESS operation, and how to consider BESS degradation in the objective function?
What is the additional profitability obtained when providing simultaneously BTM and FTM services, e.g., when participating in day-ahead wholesale electricity market and frequency regulation markets, with respect to providing BTM service only?
What is the impact of considering a dynamic operation strategy for market participation, with BESS state of charge (SoC) changing continuously (every 15 minutes) to follow the volatility in electricity prices, renewable generation, and demand, with respect to a strategy with fixed SoC (fixed daily, monthly, yearly) for market participation?

Deliverables

Final report including:

Technical insights on the core functionality of a VPP aggregator, their business model, and the system layout for integrating energy storage assets within wider VPPs.
Description of the mathematical formulation of the optimization algorithm.
Assessment of the additional BESS profitability achieved by providing FTM services in addition to BTM services.
Assessment of the impact of battery degradation on BESS profitability.

Python-based code implementing the optimization algorithm for determining optimal operation strategies across all scenarios of interest:

BTM services only.
BTM + FTM services with fixed daily, monthly, yearly SoC.
BTM + FTM services with and without battery degradation.
BTM + FTM services for participation in different markets of interest.Key Skills

Expertise Required

Ideally, the students will build upon the following skills:

Strong foundation in quantitative modeling and algorithm development, specifically within the domains of mathematical optimization and data-driven decision-making.
Experience with quantitative modeling and decision-making algorithms applied to the optimal control and dispatch of battery energy storage systems.
Knowledge of European electricity markets, including wholesale and ancillary service markets.
Knowledge of battery energy storage systems, including state of charge, state of health, voltage and temperature evolutions, and their application scenarios.
Proficiency in programming in Python, as well as in mainstream optimization frameworks such as pyomo, cvxpy, or similar.

References

Loßner, M., Böttger, D., & Bruckner, T. Economic assessment of virtual power plants in the German energy market — A scenario-based and model-supported analysis. Energy Economics, 62, 125-138 (2017).
Braeuer, L., Rominger, J., McKenna R. & Fichtner W. Battery storage systems: An economic model-based analysis of parallel revenue streams and general implications for industry, Applied Energy, 239, 1424-1440 (2019).
Srinivasan, A., Wu, R., Heer, P. & Sansavini, G. Impact of forecast uncertainty and electricity markets on the flexibility provision and economic performance of highly-decarbonized multi-energy systems, Applied Energy, 338, 120825 (2023).

Partners: Jura Materials

Contacts: Joel Zürcher, Marcel Bieri

General Description and Problem Formulation

Jura Materials is a leading building materials provider in Switzerland. It operates an aggregate, landfill, ready-mixed concrete, and a cement fleet. The transport of these materials consumes more than 2’000’000 liters of diesel annually. This corresponds to 5’300 tonnes of CO2 emissions. The goal is to mitigate these emissions by electrifying the fleet in the coming years. Jura Materials operates 30 different locations all over central and northern Switzerland.

The challenge is to make this transition in a most efficient way by analysing material transfer routes, applying a novel logistic strategy incorporating the boundary conditions that electrified transport brings to the table, considering the local and geographical characteristics of each transport route.

Research Questions

What is the end state of an optimized, electrified logistics?
What does the transformation look like on a timeline?

Deliverables

A report describing:

the situation at hand, state of the art technologies
the methodology / key assumptions
the derived objective function to reach the desired end state
the derived timeline for the transformation
Cost of transformation vs. 100% Hydrotreated Vegetable Oil (HVO) diesel in terms of Invest (CAPEX) and operational cost (OPEX)
Results and discussion including analysis of the sensitivity for key assumption parameters (electricity price, cost of invest, funding, subsidies)

Expertise Required

Quick learning
Joined-up thinking
Thinking outside the box
Basic economics (Profit & loss calculations)
Basic engineering (electrical), (optional)

References

https://www.bfe.admin.ch/bfe/de/home/foerderung/dekarbonisierung/ausschreibung-ladeinfrastruktur-e-lkw.html (funding)
https://www.srf.ch/news/schweiz/abgabe-fuer-lastwagen-e-lastwagen-sollen-auch-schwerverkehrsabgabe-zahlen (subsidies)
https://www.swissinfo.ch/ger/weltgroesstes-elektrofahrzeug-nimmt-im-berner-jura-fahrt-auf/44063028 (for inspiration)
https://www.tagesanzeiger.ch/elektromobilitaet-schweiz-lkws-und-toeffs-mit-startproblemen-232452361316 (for inspiration)

Partner: MMG Management Consulting, Aurora Energy Research

Contacts: Andri Lang, Arnaud Oltramare, Luz Hitters

General Description and Problem Formulation

Battery storage is becoming a crucial element in the European power system, enabling flexibility, grid stability, and integration of renewables. The business case for utility-scale batteries depends on diverse revenue streams, ranging from energy arbitrage in wholesale markets to providing ancillary services such as frequency containment and restoration reserves. In Switzerland, new platforms (e.g. PICASSO) and regulatory decisions are reshaping these markets, while volatility and market saturation create uncertainty for future projects.

The challenge is to understand how much revenue a large-scale battery (10 MW) could generate in Switzerland “today” (2023 - 2024), and what this implies for a new 10 MW battery project starting operation in 2026. You will have to analyse historical revenue opportunities, assess market trends, and build scenarios (e.g. BESS commissioned in 2026 vs 2029) to project forward-looking profitability. This requires combining technical knowledge of market mechanisms with economic modeling and sensitivity analysis. The output should help determine whether a utility-scale battery remains an attractive investment in the future under different assumptions.

Research Questions

Historical Analysis – What is the estimated breakdown of annual revenues for a utility-scale battery in 2023 and 2024?

Quantify and break down annual revenues of a utility-scale BESS across:

Day-ahead market
Intraday market
FCR (frequency containment reserve)
aFRR (automated frequency restoration reserve)
Other reveneus streams (e.g. Inertia, reactive power)

Forecasting: How financially viable is a utility-scale battery entering the market in 2026?

Include scenario-based projections considering:

The development of market price forecasts
How different opportunity costs affect dispatch decision of a battery trader
Market saturation
Volatility/spreads trends
Grid connection fee and grid connection request
Regulatory or policy changes

Deliverables

1. Historical Analysis Results

Calculate yearly average prices for FCR and aFRR capacity in 2023 and 2024.
Calculate yearly average daily spreads in the day-ahead and intraday markets for 2023 and 2024.
Model historical battery dispatch revenues using the price series as input.

Suggested format: line charts over time for prices and spreads

2. Forecasting Outputs

Model the yearly average prices for FCR based on your historical analysis (deliverable 1.1) until 2040
Model the yearly average daily spreads in the day-ahead and intraday markets based on your historical analysis (deliverable 1.1.) until 2040
Model forecasted battery dispatch revenues using the forecasted price series as input

Suggested format: line charts over time for prices and spreads

3. Financial Model for a New 10 MW Battery (2h)

Include CAPEX, OPEX, and grid connection fees on the cost side and modelled revenues per market for the revenue side (Waterfall chart)
Calculate key financial indicators such as NPV and IRR in real 2024, pre-tax.

4. Presentation of these Key Findings

Deliver a professional slide deck that:

Summarises methods, assumptions and results▪Visualises the historical and forecasted price series
Present the Waterfall chart for a battery entering the market in 2026
Highlights key insights, risks, and recommendations

Expertise Required

Technical / Energy Systems: Knowledge of electricity markets, ancillary services, and battery operation.
Economic / Financial: Price modeling, CAPEX/OPEX analysis, and project finance (NPV, IRR).
Data Analysis: Market price data handling, time-series analysis, forecasting, and visualisation.
Policy / Regulatory: Awareness of Swiss and European balancing platforms (e.g. PICASSO) and grid connection frameworks.
Communication: Ability to deliver results in a structured, clear, and investor-relevant format.

References

Federal Office of Energy (BFE): Competence centre for issues relating to energy supply and energy use at the Federal Department of the Environment, Transport, Energy and Communications (UVEK)
Swissgrid: Responsible for managing and maintaining the entire high-voltage transmission system and ensuring the exchange of electricity with neighbouring countries
ENTSO-E: Information on PICASSO and market prices.
Elcom Switzerland: Market monitoring and reports on electricity markets
Market data sources (day-ahead and intraday prices, balancing capacity prices)

Partners: MMG Management Consulting, ewz

Contact: Catherine Martin-Robert, David Heller, Christian Bosshard, Luz Hitters

General Description and Problem Formulation

A pre-construction energy yield assessment report for wind farms providesestimates of the gross energy production based on wind measurements, machinetype and various extrapolations. Additional technical and environmental losses arealso predicted, and an uncertainty assessment is conducted to determine the netelectricity production in MWh. Based on our monitoring system, some parks showlower effective electricity production than the studies suggest. While most of thelosses are easy to analyse (availability, electrical efficiency, turbine performancelosses, environmental losses and curtailment losses), the deviation in the forecastedgross production is much more difficult to analyse and is mainly due to long-termwind prediction and the influence of other turbines (wake effect). Systematicallyanalysing each parameter and its dependencies would help to understand thereasons for these deviations.

Research Questions

How do the parameters of each pre-construction energy yield assessment reportcompare to those in operation?
What are the differences and reasons for the discrepancy between the estimatedgross electricity production (without losses) and the actual gross production?
What are the differences and reasons for the discrepancy between the net production baseline and the net effective production?

Deliverables

A report specifying the methodology and quantitative and qualitative results of theanalysis (tables, charts, etc).

Expertise Required

Data Analysis & Statistical Skills

Ability to analyze and aggregate sets of theoretical and operational data
Understand essential information from detailed reports

Technical Skills

Basic understanding of the functionality of a wind turbine

Deviation Analysis / Root Cause Analysis

Ability to decompose gross-to-net yield losses (Electiricty in MWh)
Modeling assumptions vs real-world behavior

Reporting and Communication

Ability to prepare clear, structured reports for technical and non-technicalstakeholders
Translate statistical findings into business or operational insights
Effective data visualization (e.g. Power BI, Tableau, etc.)

Partners: MMG Management Consulting, Vattenfall

Contact: Sebastian Glibic, Dr. Igor Dakic, Luz Hitters

General Description and Problem Formulation

April 2024, Germany has announced the introduction of a capacity market (CM) in 2028. After more than 10 years of rumors about this topic, in October 2024 there is an announcement on the capacity mechanism design. Then the coalition breaks.

Now new assessments are made and Vattenfall is contributing their perspective. The EU provides a clear framework [CISAF] in which Germany can create a CM. Different markets provide examples for operational CMs and enable insights on the effectiveness of these mechanisms.

Generally, there are different perspectives on the topic, broadly separating between operators/investors (provide capacities) and grid operators (procure capacities).

The government wants to find a suitable solution to serve 4 main objectives: 1. Ease of administration, 2. Openness to innovation, 3. Security of supply and 4. Long-term investment incentive.

Vattenfall acts as a potential capacity provider and is interested in using potential revenues to enable long-term investments in fossil-free capacities — predominantly in batteries, but also in pumped hydro storage and hydro generation. Other countries have encountered difficulties and unstable mechanisms; recent news from the UK reports that battery operators are opting out of their contracted obligations. It is always a trade-off between innovation and security, balancing administrative effort with efficiency. The challenge lies in creating an efficient mechanism that can effectively address supply issues that the market fails to resolve on its own.

Research Questions

What can Germany learn from other countries when it comes to achieving the above 4 goals? How can cost effective investment incentives be in alignment with the green deal framework of the EU? What are relevant considerations for capacities to participate in a capacity market?

Deliverables

The outcome should formulate current status quo of the capacity market design in Germany, does it adapt setups from other countries or does Germany go their own way? Outline different dimensions for the 4 main objectives and caveats and flaws in the design from the perspective of a fossil free capacity provider Vattenfall aims to become (here it is expected to outline pros and cons of different dispatchable capacities). Investigate on the potential trade offs to participate in such a scheme. Here it helps to learn more about the UK market and why Battery operators opt out.

Expertise Required

Energy market knowledge such as different market designs [energy only market, capacity markets]. Investment background, different quality of income streams and their effect on a risk profile for planned investments. Analytical skills. Energy storage knowledge and broader energy system stability mechanisms.

References

UK Capacity Market Reform & Battery Participation National Grid ESO. Capacity Market Auction Results & Derating Factors. https://www.emrdeliverybody.com
Germany’s Combined Capacity Market (CCM) Proposal Bundesministerium für Wirtschaft und Klimaschutz (BMWK). Strommarktdesign 2030 – Diskussionspapier zur Einführung eines Kapazitätsmechanismus. https://www.bmwk.de
EU Green Deal Investment Framework European Commission. Financing the Green Deal – Investment Plan and Just Transition Mechanism. https://ec.europa.eu/green-deal
EU Funding Instruments for Energy Transition European Commission. Recovery and Resilience Facility, Modernisation Fund, InvestEU. https://ec.europa.eu/info/business-economy-euro/recovery-coronavirus/recovery-and-resilience-facility_en
Lessons from Other EU Capacity Markets ACER & CEER. Annual Report on the Results of Monitoring the Internal Electricity Market. https://www.acer.europa.eu
Battery Storage Revenue Trends in UK LCP Delta. Battery Storage Revenue Benchmarking Report. https://www.lcpdelta.com
Clean Power 2030 Initiative UK Department for Energy Security and Net Zero. Clean Power 2030 Strategy. https://www.gov.uk/government/publications/clean-power-2030

Partners: ShareP AG - Sustainable Parking Management

Contact: Mateusz Wojdylo, Remy Banghard

General Description and Problem Formulation

Urban mobility is in transition. Parking demand is highly variable, yet most locations still rely on static pricing models that don’t reflect actual demand, congestion, or sustainability goals. This creates inefficiencies: drivers circle looking for cheaper spots, EV charging is not incentivized, and property owners lose revenue. ShareP operates digital parking and EV charging infrastructure for major corporates and cities. The challenge is to design a dynamic pricing model that balances economic performance, user convenience, and sustainability objectives (e.g., reducing car usage, encouraging EV adoption, promoting off-peak travel).

Research Questions

What dynamic pricing mechanisms (time-based, demand-based, sustainability-based) are most effective for balancing demand and supply in urban parking?
How can AI/ML methods be used to predict parking occupancy and adapt pricing in real time?
How should pricing models integrate sustainability incentives (e.g., lower prices for EVs, car-sharing, or off-peak usage)?
What are the expected impacts on user behavior, CO₂ reduction, and revenue for property owners and cities?

Deliverables

A prototype dynamic pricing algorithm (simulation or software prototype).
A case study report analyzing at least one real-world ShareP location in Zurich/Basel, including data-based simulations of different pricing strategies.
Clear KPIs and dashboards for evaluating success (revenue, utilization, emissions avoided).
Policy and user behavior recommendations to make dynamic pricing acceptable and impactful.

Expertise Required

Technical: Data analytics, optimization modeling, machine learning.
Economic: Pricing strategy, behavioral economics, mobility economics.
Sustainability: CO₂ accounting, urban mobility policy.
Coding: Python/Matlab or similar for simulations and visualization.

References

ShareP case studies (Zurich, Basel, Munich).
Academic research on dynamic pricing in mobility (parking, ride-sharing, public transport).
City of Zurich Smart Mobility initiatives & EU Green Deal targets.
Behavioral economics literature (e.g., Richard Thaler, Rory Sutherland).

Partners: Solar Taxi Ghana

Contact: Agusto Espinel, Inga Nienkerke, Mashael Yazdanie

General Description and Problem Formulation

The global transition to electric mobility creates a vast supply of used vehicle batteries retaining 70-80% of their original capacity. The most reliable strategy for this resource is creating de-rated, low-power second-life systems, maximizing their remaining lifespan. This opens a great opportunity for low-cost energy in regions across the Global South, suited for powering small scale applications such as a micro-enterprise or a rural home's essential appliances. Crucially, emerging EV fleets in many of these regions have a high share of electric motorcycles and three-wheelers, ensuring the future supply will consist of a high volume of small, low-voltage packs for these applications.

A critical bottleneck, however, prevents this circular economy from scaling: the lack of a fast, affordable field tool and process to assess and sort these varied cells into standardized, reliable, low-voltage battery packs.

This project challenges students to develop this technology and the guidelines for its deployment and use.

Research Questions

How can we create a simple and affordable tool that empowers local technicians to test and rebuild used EV batteries, giving them a second life as a reliable power source?
How can a rapid diagnostic cycle accurately and cost-effectively predict a cell's performance and remaining lifespan?
What is the optimal hardware and software architecture for a field kit that guides technicians to not only grade cells, but to specifically build small, reliable, low-voltage modules from a mixed supply of used EV cells?
What algorithms can recommend optimal module configurations that minimize intra-unit variance, ensuring safety and longevity for typical Second Life Battery (SLB) use cases?

Deliverables

Physical Hardware: A portable, low-cost device for safe, low-power diagnostic testing of individual cells.
Software Application: A user-friendly app providing State of Health (SOH) analysis. It will feature pre-loaded "Pack Blueprints" to guide technicians in building standardized, reliable low-voltage systems for specific use cases.
Comprehensive Documentation: A full technical report justifying the reliability-based design, including schematics, a low-cost Bill of Materials (BOM), and all source code, paired with a simple, visual user manual for technicians.

Expertise Required

Technical (Hardware): Electrical engineering, circuit design, sensor integration, microcontroller programming.
Technical (Software): Strong programming skills (Python, C++), data analysis, UI design.
Domain Knowledge: Understanding of battery principles, degradation mechanisms, and the principles of de-rating for extending cycle life.
General: Creative problem-solving, user-centered design thinking, teamwork, project management.

References

external page This video highlights the international recognition of Solar Taxi's work in Ghana, with the Swiss Transport Minister commending their efforts in providing affordable electric vehicles.
external page This study establishes electricity as a direct and essential input for vendors' work. It highlights the critical need for a stable, continuous power source to sustain livelihoods in Accra, Ghana.

Partners: Verkehrsbetriebe Zurich (VBZ)

Contacts: Fabio Inderbitzin, Geoffrey Klein

General Description and Problem Formulation

Electric buses are equipped with high-resolution data logging systems that capture detailed information such as pedal position, acceleration, and steering angle. This data creates opportunities to explore patterns in driving behavior and its potential impact on energy consumption. If differences in driving styles can be identified and shown to significantly influence efficiency, transport operators could consider targeted feedback systems or training measures to improve performance.

For the energy optimized driving, it might be worth mentioning that this applied to the already difficult area of urban transportation in which the buses are sometimes in traffic and station stops are close together. Driving style optimization on conventional railway is well known and works.

For this challenge, students can investigate how driving styles manifest in data and whether they correlate with variations in energy consumption. They may choose to explore market and patent research on relevant driver assistance and feedback technologies, evaluate technical and operational feasibility, or develop concepts for potential implementation.

Research Questions

Can driving styles be identified from high-resolution e-bus data (pedal use, acceleration, steering, etc.)? Students may choose to experiment with clustering, machine learning, or statistical approaches.
What is the measurable impact of different driving styles on energy consumption and efficiency? Exploration of correlations and influencing factors.
Which technological or operational solutions could support drivers in improving energy-efficient driving? Optional focus on technologies, feedback systems, or training approaches.
What opportunities and challenges arise when integrating such solutions into daily bus operations? Consideration of feasibility, costs, and acceptance.

Deliverables

Students can prepare a project report or alternative outputs depending on their chosen approach. Possible deliverables include:

Data analysis and visualization of driving style patterns.
Quantitative assessment of energy impacts under different conditions.
A review of existing technologies or patents related to driver feedback and efficiency tools.
Concepts for potential applications (technical solutions, training, or feedback mechanisms).
A short presentation or demo summarizing findings and recommendations. The exact scope and format are flexible — students may decide based on feasibility, interest, and available resources.

Expertise Required

Data Analysis: Handling high-resolution sensor data, clustering methods, statistics, or machine learning.
Technical Understanding: Basics of vehicle dynamics, electric propulsion, and energy consumption.
Research/Innovation: Technology scouting, patent review, evaluation of driver feedback systems.
Strategic/Economic: Understanding potential cost savings and operational impacts.
Communication: Clear visualization of data and presentation of insights.

Partners: Verkehrsbetriebe Zurich (VBZ)

Contacts: Fabio Inderbitzin, Geoffrey Klein

General Description and Problem Formulation

Public transport operators across Europe are transitioning their bus fleets to electric vehicles. While technical feasibility and vehicle availability are rapidly improving, the economic viability of e-bus operations strongly depends on energy costs. In Switzerland, local electricity tariff structures differ significantly between municipalities, with variations in energy price levels, peak-load charges, and time-of-use models. For operators like VBZ, these local differences can substantially influence charging strategies, infrastructure investments, and ultimately the total cost of ownership (TCO) of e-buses.

The challenge is to systematically analyze how varying local tariff models affect charging costs and operational decision-making. By simulating different charging strategies under real tariff conditions, students can assess economic implications and derive recommendations for procurement and charging policies. This analysis may provide operators of electric buses with strategic insights into how tariff structures may shape the electrification roadmap of the bus fleet.

Research Questions

How do local electricity tariff structures (e.g., time-of-use pricing, demand charges, peak-load tariffs) vary across selected municipalities? Comparison and categorization of representative tariff models.
What impact do these tariff structures have on charging strategies for e-buses? Simulation of overnight, opportunity, and mixed charging strategies under different tariffs.
How do resulting charging costs affect the total cost of ownership (TCO) and operational decisions (e.g., fleet size, charging infrastructure investments)? Identification of cost drivers and sensitivity to tariff parameters.
What strategic recommendations can be derived for electric bus operators regarding charging policies and procurement decisions? Guidelines for optimizing charging strategies and infrastructure planning.

Deliverables

The students could produce a comprehensive analysis report supported by quantitative modeling. The report could include:

A comparative overview of electricity tariff models from selected municipalities.
Charging simulations for different strategies (overnight, opportunity, hybrid) under these tariffs.
A TCO calculation framework showing cost differences across scenarios, including sensitivity analysis for key parameters.
Identification of economic break-even points for different strategies and tariff structures.
Strategic recommendations for VBZ on optimal charging and procurement approaches.
A final presentation summarizing results, methodologies, and actionable insights.

Expertise Required

Technical/Engineering: Knowledge of electric mobility, charging infrastructure, and energy systems.
Economic/Analytical: TCO modeling, cost-benefit analysis, and sensitivity analysis.
Simulation/Modeling: Ability to design and implement charging strategy simulations (e.g., Excel, Python, or specialized tools).
Policy/Strategic: Understanding of local energy regulations, tariff design, and implications for public transport planning.
Communication: Clear reporting and presentation of complex technical and economic findings.

References

Partners: Verkehrsbetriebe Zurich (VBZ)

Contacts: Fabio Inderbitzin, Geoffrey Klein

General Description and Problem Formulation

The Zurich Public Transport operator (VBZ) operates the external page InnoTram, a test platform based on a Cobra tram. The purpose of the InnoTram is to pilot and validate new technologies related to operations, passenger comfort, and maintenance, while the tram is normally operated. However, there is currently no systematic approach to capturing and evaluating available innovations. While startups, established industry partners, and universities continuously develop promising solutions, their potential for tram and urban mobility often remains untapped.

The challenge is to conduct a structured market research within a limited timeframe, identify technological trends, and filter out the most promising solutions. The focus is not only on technical feasibility but also on regulatory and operational considerations as well as cost. Students are expected to prepare these findings in a way that allows VBZ to make informed decisions about possible pilot implementations or collaborations. This project directly contributes to the innovation strategy and future readiness of VBZ.

Research Questions

Which relevant technologies currently exist on the market or in development that could benefit the InnoTram and urban mobility? With focus areas such as sensor technology, passenger information, energy management, predictive maintenance, or smart-city integration.
How can these technologies be integrated into existing tram infrastructure (Cobra/InnoTram) from a technical and operational perspective, and what would it cost? Assessment of interfaces, technology readiness, and required adaptation efforts.
What legal, regulatory, and organizational aspects need to be considered for an implementation? Evaluation of standards, safety, data protection, and passenger acceptance.
Which cooperation and business models are suitable for collaborating with startups, universities, or established providers? Analysis of partnerships, pilot projects, or innovation platforms.

Deliverables

The students could produce a comprehensive scouting report that systematically presents which technologies show potential for the InnoTram. The report could include:

A structured overview (e.g., matrix or mapping) of the identified technologies.
Short profiles of the most promising technologies (function, application examples, providers, etc.).
A feasibility assessment for integration into the Cobra/InnoTram, including opportunities and risks.
Cost estimates (order of magnitude) for potential pilot applications.
Recommendations for collaboration models and potential partners (startups, industry, research).
A final presentation of the results for the VBZ innovation team, summarizing the key insights and proposing concrete next steps.

Expertise Required

Economic/Strategic: Market and competitor analysis, business models, cost estimation.
Analytical/Research: Technology trend analysis, structured evaluation methods.
Communication: Preparing clear reports and presenting findings to a professional audience.

References

external page https://www.stadt-zuerich.ch/vbz/de/mobilitaet-im-wandel/innotram.html

Partners: Verkehrsbetriebe Zurich (VBZ)

Contacts: Fabio Inderbitzin, Geoffrey Klein

General Description and Problem Formulation

Electric buses operated by VBZ generate large amounts of high-resolution data, capturing technical parameters, operational conditions, and usage patterns. While this data is already valuable for internal fleet management, its broader potential for innovation, research, and policy-making remains largely untapped. Possible applications could range from predictive maintenance and energy optimization to urban planning, sustainability reporting, or academic collaborations. In this challenge, students can explore and propose potential use-cases for this data. They may choose to formulate and evaluate a broad set of possible applications across stakeholders (VBZ, academia, policymakers, the public), or focus on a single use-case and carry out a deeper analysis.

Research Questions

Which promising use-cases for high-resolution e-bus data can be identified across different stakeholder groups? Consider technical, operational, societal, and policy-relevant dimensions.
What added value could these use-cases generate for VBZ and/or external stakeholders? Evaluation of benefits, risks, and alignment with sustainability goals.
What challenges (technical, legal, ethical) would need to be addressed to unlock these use-cases? Attention to data protection, system integration, and stakeholder acceptance.
How might one selected use-case be implemented and evaluated in practice? Optional deep dive into feasibility, methodology, and potential outcomes.

Deliverables

Students can choose the format and scope of their work. Possible deliverables include:

A catalogue of use-cases with stakeholder mapping and value assessments.
A conceptual evaluation of selected use-cases, including feasibility, challenges, and expected impact.
A focused analysis or prototype (e.g. data visualization, small-scale model, or methodological framework).
A short presentation summarizing findings and potential next steps. Flexibility is encouraged — students may define their own angle based on feasibility, interest, and creativity.

Expertise Required

Data/Analytics: Understanding of high-resolution data, basic analysis methods, visualization.
Strategic/Innovation: Creativity in identifying novel applications, stakeholder mapping, business case thinking.
Technical/Operational: Familiarity with e-bus systems, fleet operations, and transport engineering.
Legal/Ethical: Awareness of data protection, privacy, and ethical implications.
Communication: Clear documentation and presentation of concepts.

Partners: VERBUND AG

Contacts: Florentine Gruber, Lukas Titton

General Description and Problem Formulation

VERBUND, Austria’s largest electricity company, has entered into a cooperation with the external page Technical Museum of Vienna to showcase the energy future and its challenges in a dedicated exhibition space, in particular the need for flexibility, sector coupling and energy storage. The energy transition is one of the biggest challenges of our time; the more people understand its impact, the better.

VERBUND plays an active role in shaping a renewable and sustainable energy future. It has a legacy in energy storage and works on innovative concepts for providing flexibility.

The goal of the challenge is to create a concept or even a prototype of an exhibit piece that covers the topic “flexibility & energy storage” for the visitors of the museum. The prototype will be 1 out 5 exhibit pieces and is supposed to be displayed in the “external page innovation corner” of the museum. Only limited space will be available therefore the piece must adhere to certain measures.

Research Questions

What: Create a concept or even prototype that captures the interest of visitors and lets them explore innovations in the field of energy storage and flexibility, tailored towards either a young audience (Gen Z and Alpha).

Deliverables

The deliverable should include a well-developed concept for a prototype, and if time permits, we encourage you to create an initial physical prototype. You have the freedom to be creative while working within the spatial constraints of the exhibition area. If all parties involved are satisfied with your concept, it will be incorporated into the exhibition and showcased live in the museum for a period of 4-6 months.

Exhibit Piece Criteria:

Target Audience Engagement

Age-appropriate: The exhibit piece must be designed to appeal to a young audience (Generation Z and Alpha)
Interactive Elements: Integration of interactive components that spark curiosity and encourage experimentation. However, bear in mind that potential interactive elements must be self-explanatory and do not require a lot of maintenance or a person who assists.

Simplicity of Presentation

Intuitive Symbols: Use of easily understandable symbols and icons to convey concepts (e.g., storage, flexibility).
Minimized Text: Avoidance of extensive explanatory texts, using instead short, concise descriptions or labels.

Educational Aspect

Clear Concepts: Providing clear, basic information about energy storage and flexibility without complex jargon.
Connection to Everyday Life: Demonstrating the relevance of the topic to the visitors’ lives, for example, through examples from their own environment.

Innovative

Displaying innovations in the field of energy storage and flexibility should be the core focus of the exhibit piece.

Expertise Required

Technical expertise: understand the technologies for providing flexibility in the electricity system such as storage, sector coupling etc
Expertise in energy economics: understand the interplay of energy markets, mechanisms and limitations
Expertise in regulatory issues and policies: understand the regulatory toolbox
Creativity: thinking beyond the usual and implementing elements which catch the eye and the interest of the audience

References

Find out more about VERBUND´s innovation initiatives: external page VERBUND X - learn everything about us and what we do

Innovation Corner current exhibition: external page Innovation Corner: Young ideas | Exhibition | TMW