Master Thesis

The benefits of energy storage technologies in order to manage intermittent renewable energy generation from solar PV are well documented. However, Electric Vehicles (EVs) present a unique opportunity to substitute the need for stationary batteries, given that they are parked for long hours. This master thesis seeks to compare the techno-economic performance of PV systems with EV loads against stationary battery systems, both at the individual household and energy community levels. Using real-world data on PV production, household electricity demand and mobility behaviour of individuals with car, a techno-economic model will be formulated. Scenario exploration with EV-user types will further allow the assessment of specific mobility patterns that may achieve comparable or even higher performance as compared to stationary batteries.
Tasks:

• Literature Review – PV+Battery Systems, PV+EV
• Formulation of new/extension of existing techno-economic model (Python)
  Formulation and analysis of multiple scenarios of Battery and EV uptake

Requirements :

• Programming and data analysis skills, ideally Python
• Interest in the energy transition to tackle climate change
• Knowledge of or interest in learning about the electricity system and electricity markets

Traveling by airplane is the fastest but the most CO2-intensive mode of travel. However, there are many less-emitting options like buses, coaches and trains connecting the most popular destinations within Europe (and even worldwide). While in some cases the travel time is vastly longer by other means as compared to air travel, there exists a high potential to reduce air travel between well-connected destinations that are not very far apart. This thesis aims to study and implement ways to promote the choice of rail (or other greener) travel over air travel. A key focus is on establishing whether individuals clearly account for the total travel times: Airports are typically further away from the city and air travel requires a protocol-heavy, time-consuming procedure that precedes the journey, accounting for which the total time saved by the ‘faster’ travel mode may not be as high as assumed.
Tasks:

• Literature review on factors affecting travel mode choices
• Design and implementation of a digital tool/survey to collect information on participants’ perceptions of travel time
• Quantitative data analyses

Requirements :

• Basic quantitative data analytics skills in R/python
• Interest in human behaviour, climate change and transport

The share of Electric Vehicles (EVs) is projected to grow in the future. Studies have shown that uncontrolled charging of EVs may lead to electric grid stability issues and increased demand fed by fossil fuels. Controlled charging of EVs (reduction/increase in the rate or level of charging or shifting of charging process times) will be necessary to maintain grid stability and consume electricity from renewable energy sources, to decarbonize transport. However, EV users’ preferences are necessary to execute such controlled charging practices. This master thesis aims to conduct surveys to collect real EV-user’s preferences on EV charging, inclusive of mobility behaviour and charging habits, as well as EV users’ preferences for varied controlled charging practices. The results may prove useful in estimating the realistic flexibility potential that can be derived from EVs, and help electricity system operators maintain grid stability and increase the consumption of renewable energy sources.
Tasks:

• Literature Review on EV User Preferences for Controlled Charging
• Survey Design and Data Collection, Analysis

Requirements :

• (Preferable) Experience with/courses attended about Qualitative Research Methods
• (Preferable) Language skills in German
• Interest in mobility, electric vehicles and climate change mitigation

People have varied mobility profiles and varying EV charging preferences. Using agent-based models of heterogeneous driver types, this master thesis aims to analyse the impact of EV charging on the electricity network under different mobility behaviour profiles and different driver preferences on charging and battery levels. Key research questions to answer using such a model may be:

• How do varying user preferences impact the volume of EV charging?
• What incentives may be provided to EV users in order to adjust EV charging times to benefit the electric grid?

The market for personalized nutrition is increasingly growing. Nutrition or fitness apps promise their users better results by taking their individual needs and characteristics into account. Digital transformation offers the opportunity to collect a variety of data about users and to profitably incorporate this knowledge into the business. By taking data into account, offers can be designed in a more targeted manner. Research shows that considering the heterogeneity of target groups through personalized approaches such as tailored recommendation systems or personalized nudges can successfully increase consumer purchase intent (Mills 2020).

The task of this master’s thesis is to identify and analyze approaches to personalization in the food industry. Special attention should be paid to the importance of digital technologies. in addition to a discussion of the literature, a methodical examination of the topic is expected. This can be done with the help of case studies or interviews.

Many companies in the food industry, such as payback, Lidl, Aldi and Rewe, offer loyalty card programs to consumers. This allows them to collect a variety of data about consumers and their shopping behavior. From a research (and policy) perspective, it is of interest to assess the data quality of the data collected by these companies. Questions to be addressed in this context include the structure of the data and its potential usefulness for personalized recommender systems. Of additional interest is the extent to which companies can draw conclusions about consumers’ lifestyles from the data they collect.

The task of this master’s thesis is to evaluate the data quality of different loyalty card providers in a self-trial.

Study results show that consumers generally find it difficult to link their consumption behavior to environmental problems. Among other things, the impact of meat consumption on sustainability is not always perceived by consumers (Ortiz, Reisch 2022). Behavioral economics can help to make the impact of meat consumption more salient to consumers. The digital context, in particular, offers the opportunity to show consumers the consequences of their behavior instantly.

The task of this master’s thesis is to conduct an experiment in which the consequences of meat consumption are made more salient and to investigate the impact of such an approach on the consumption of the participants. For this purpose, an online supermarket is available in which different behavioral tools like social norms or real-time feedback can be established and tested.