Student thesis | Techno-economic evaluation of business models for battery storage and renewable energies
Are you interested in a topic that really moves the energy industry?
Do you want to evaluate business models in the field of battery storage from a technical and economic perspective?
The expansion of renewable energies is leading to increasing demands for flexibility in the energy system. Battery storage systems play a central role in balancing supply and demand and stabilising electricity grids. At the same time, new business models for storage systems are emerging - for example through co-location with renewable energies or through participation in various electricity markets. As part of this work, business models for battery storage systems are to be evaluated technically and economically and their potential in the future energy system analysed. The focus of the project or final thesis can be customised in consultation with the supervisor.
Possible tasks are
- Scientific literature research (conducting a literature review)
- Development of a model in Python/PyPSA
- Data analysis and evaluation
- Derivation of recommendations for action
Supervisor: Prof. Dr.-Ing. Jens Schneider, M.Sc. Anna Luna Hofmann
Responsible university lecturer: Prof. Dr.-Ing. Jens Schneider
Call for applications: Interested in research? (PDF)
Student project | Solar drinking water treatment
The treatment of drinking water using 100% solar energy has many exciting fields of application, especially in dry, sunny regions of the world. The dynamic energy distribution of finite energy in a complex system is also an exciting special case of the operation of flexible energy systems under strongly fluctuating energy prices that reflect a high or low supply.
In a Python-based model, a dynamic distribution of the solar energy supply to different consumers of a robust multi-stage flash water treatment process is calculated. At the same time, a laboratory-scale test setup is planned.
The specific tasks are as follows:
➤ Development of a dynamic simulation environment in Python-based frameworks (e.g. TesPy).
➤ Optimisation of energy distribution in the system.
➤ Planning of a test setup on a laboratory scale.
University lecturers responsible: Prof. Dr Jens Schneider
Student thesis | Micro-merit order control for energy systems
Sector coupling through the electrification of heat, mobility and industrial supply through heat pumps, electromobility and hydrogen electrolysis increases the demand for electricity. The increased demand for electricity leads to an increasing need for electricity grids. Intelligent grid utilisation that takes supply, demand and grid utilisation into account can reduce the need to expand the grid. The HTWK is developing intelligent grid utilisation based on local merit order processes. The smart micro-merit order control is being continuously developed.
Specific tasks are as follows:
➤ Further development of the merit order simulation in Python.
➤ Evaluation of the states and potentials in the simulation.
➤ Development of intelligent measures to improve the bidding strategies of market participants.
➤ Comparison of future scenarios.
University lecturer responsible: Prof. Dr Jens Schneider
Student project | Creation of an electricity price forecasting tool
Energy prices have been subject to extreme fluctuations in recent years. For a better understanding of such effects and forecasts for further development, taking into account the expansion and dismantling of generation capacities as well as a change in electricity demand, a simulation tool is being created that calculates the merit order based on the power plant list, taking into account fuel and CO2 costs.
A similar tool (GEMCast) has already been created at the HTWK. Based on this work, the tool will either be updated or newly created. The programming is done in Python.
By working on this project, students will gain a deep insight into the price mechanism of the merit order on the electricity exchange and the cost calculation of electricity. Previous knowledge of the energy market and especially Python programming is helpful.
Specific tasks are:
➤ Creating cost models for different power plants.
➤ Creating a model for mapping the merit order.
➤ Creating a user interface for analysing data such as electricity price and energy mix as well as scenario creation.
➤ Comparison of future scenarios.
University lecturer responsible: Prof. Dr Jens Schneider
Student work | Live cost calculator for different coloured hydrogen
Hydrogen is currently on everyone's lips. The different colours of hydrogen reflect the type of production; green hydrogen is produced by electrolysis using renewable energies, grey hydrogen from natural gas by steam reforming, blue hydrogen with additional CO2 capture, etc.
The current price developments on the energy market, particularly for gas, coal, CO2 and electricity, were not foreseen by anyone. From today's perspective, nobody can predict how prices will develop. However, these prices are also decisive for the costs of the various types (colours) of hydrogen production. In order to be able to take into account the unpredictably fluctuating prices, an online hydrogen price calculator with self-adjustable costs is being created as part of this work. This allows the influence of changing price components (energy, technical equipment) on the costs of the various hydrogen colours to be determined and adjusted on a daily basis.
The work will focus on the following areas:
- Familiarisation with the colour theory of hydrogen.
- Familiarisation with the cost accounting of the different types of hydrogen production.
- Creation of a cost accounting tool taking into account existing procedures and standards (e.g. VDI 6025).
- Integration on the HTWK website.
- Discussion of sensitivity by cost factor.
Supervisor: Robin Pischko
Responsible university lecturer: Prof. Dr.-Ing. Jens Schneider
Student project | Automated data analysis for Energyplan using Python (Sankey diagrams, statistics)
The Energyplan software from Aalborg University can be used to simulate current and future energy systems. Energyplan has been used in the "Simulation of networked energy systems" module for several years to understand the German government's climate targets for 2030 and 2045.
The aim of this project is to improve and simplify the data analysis from Energyplan. In addition, a comparison of several models with a statistical evaluation is to be made possible. For the evaluation, a Python programme is to be created with which Energyplan models can be evaluated and the results analysed in a freely selectable form.
By completing this project, students will gain an in-depth insight into energy system simulation and the statistical analysis of data. Previous knowledge of Energyplan and Python programming is helpful.
Specific tasks are as follows:
➤ Creating a Python code for the automatic evaluation of models with Energyplan.
➤ Displaying the results in various diagrams with freely selectable parameters.
➤ Generation of energy flow diagrams (Sankey diagram) from Energyplan data.
➤ Statistical evaluation and analysis of several models in Energyplan.
Supervisor: Martin Hafemann
Responsible university lecturer: Prof. Dr.-Ing. Jens Schneider
