Compact tower transformer stations

As a result of the energy transition (photovoltaics, heat pumps, electric vehicles), the power in many transformer stations is increasing. Additional smart grid system elements must be accommodated. This additional power and these elements should be installed in the existing premises if possible, since an additional transformer station or the relocation of a transformer station to a new building is very expensive. How is this being solved in densely populated regions worldwide (e.g. Japan, New York)? Can an approach from the world of tiny houses be used, with sliding elements? What measures could be used to operate the systems from the outside, e.g. fold-out exterior spaces?

The transformer stations should be divided into groups with a corresponding recommendation and cost estimate.

Cooling waste heat from cable conduit blocks in substations

The medium-voltage lines are subject to the highest loads at the substations, both in summer (photovoltaics) and in winter (heat pumps, electric vehicles). To reduce the load, both smart load control and line expansion can be considered. A third option would be to cool these heavily loaded cables to increase the maximum power and use the waste heat for heating/hot water purposes. The high-load periods in winter correspond to the electricity demand of the heat pumps: when it is cold outside, the lines in the ground become warm.

This paper aims to estimate the potential of such cooling based on one or two substations: How can cooling be achieved? What additional electrical power can be generated? What heat can be utilised and, if necessary, stored? What are the costs?

Dynamic electricity tariffs – control diagram

In order to better adapt the more volatile supply of renewable energies to demand, various countries have already introduced dynamic tariffs. The day before, by 4 p.m., the electricity prices (grid and energy) for each (quarter) hour are determined.

This work should include a flow chart showing when which measurement and control values are available, what happens in the event of deviations, how special events are taken into account (holidays, solar eclipses, etc.), and how the price incentive could be adjusted.

In a further step, the current systems of Primeo Netz AG could be examined to see if they meet these requirements and what still needs to be improved.

Intraday forecasting of various aggregates in the top-down model of the basic supply of Primeo Energie

In order to achieve the most accurate intraday forecast possible, it is necessary to try out and compare different forecasting methods for different intermediate aggregates of consumers (customer clusters) and suppliers (photovoltaics, Birskraftwerke, Kraftwerk Birsfelden, etc.). A systematic trawl through the approaches is a question of time and resources.

The new EPredict in the Robotron system offers numerous possibilities for creating forecasts – from holiday-compliant rollouts to non-linear regression and creating your own R scripts, everything is possible. Your own ideas are welcome. The benchmark is the day-ahead forecast of Primeo Energie AG. The top-down model of the energy flow calculation for the basic supply is to be understood. Advantage: professional environment to determine influencing parameters (e.g. the classic covariance-variance matrix) and forecast quality. The various forecast models and their effects are to be understood. An AI-based approach to intraday forecasting is expected.

Design and implementation of a ‘basic supply’ forecast portfolio with Power-BI

The quality of the forecast is an important factor influencing energy costs (spot market prices).

By creating a forecast portfolio or corresponding key figures for actual/target deviations in % and kWh, forecast quality targets can be defined and the success of any improvement measures can be regularly measured.

Removal of old routes and cable systems

In most replacement projects in the field of pipeline construction, old routes and cable systems laid under a cover stone are left in the ground due to the construction process. The reason for this is usually the phased approach to road construction, which is chosen in favour of traffic and residents, because the old supply lines can only be taken out of service and demolished once the new cable systems have been installed and put into operation. As a result, old cables continue to accumulate in the soil, which will have to be removed at increased expense in the future.

On the basis of currently planned projects, it should be examined which possibilities there are for removing old routes and cable systems from the ground with reasonable effort before, during or after the construction project. Can cost-effective provisional measures be used for the supply during the construction period? Can construction processes be designed differently? Are there other innovative solutions?

Integrating sustainability strategies into digital transformation processes

A paper dealing with the challenge of how companies can effectively integrate sustainability goals into their digital transformation processes. This work focuses on developing practical guidelines to help companies use digital technologies in a way that promotes both environmentally friendly and socially responsible practices. Rather than focusing solely on measurement through KPIs, this work analyses case studies and examples of best practice to identify specific strategies and methods that are effective in integrating sustainability into digital transformation initiatives. The aim is to develop a comprehensive set of recommendations to guide companies in aligning their digital efforts with their sustainability efforts. This should optimise both the environmental and social impacts of digital transformation.

Impact of digital transformation on corporate culture in the energy industry

This work aims to develop tailored recommendations for increasing acceptance and readiness for digitalisation processes among employees of different age groups and personality types. It focuses on creating communication and training strategies that are aligned with the specific needs of diverse groups to foster an inclusive and open-minded culture. The work involves analysing case studies from the energy industry to identify and adapt successful practices.

The aim is to create a practical guide to help companies create a positive atmosphere for digital change and increase overall readiness for digitalisation.

The use of artificial intelligence to optimise supporting processes in the energy industry

This paper explores the use of artificial intelligence (AI) to optimise operational processes in the energy industry. The aim is to find out how AI technologies can help to increase efficiency and effectiveness in various areas such as maintenance, customer management and other supporting processes. The project will explore how AI-based systems can be used to automate, improve decision-making and optimise processes, including their role in analysing large amounts of data for more accurate forecasting and strategic decision-making. A key part of the work will be to identify and evaluate potential use cases for the application of AI in the energy industry, with the aim of defining specific applications in which AI can offer significant added value. This thesis is aimed at students who are interested in the intersection of technology and operational efficiency and offers the opportunity to develop practical and innovative solutions for the energy industry.

Developing a framework for assessing and improving data quality in companies

The topic focuses on creating a comprehensive framework for systematically assessing and optimising data quality in business contexts. This framework should define criteria and metrics to measure various aspects of data quality, such as accuracy, completeness, consistency and timeliness. The work will propose methods to identify and analyse typical data quality issues in companies, with a focus on real business data and processes. Best practices and strategies will be developed to help companies implement measures to improve their data quality. The aim is to provide a practical guide that enables companies to maximise the reliability and usefulness of their data, thus improving data-driven decision-making.

Day-ahead prediction of power peaks in a grid area

This thesis deals with the development of a forecasting model to predict power peaks in a grid area in order to optimise the use of battery storage for so-called peak shaving. Peak shaving is a method of smoothing load peaks in the power grid in order to reduce grid load and increase grid efficiency. The focus of this work is on predicting days that are forecast as potential monthly maximums for electricity demand in order to plan the use of a battery storage system in a targeted manner. The battery storage system should only feed energy into the grid when a high peak load is forecast, in order to reduce the grid load and ensure the stability of the electricity grid.

Regionalisation of the 2050 energy strategy in the Primeo Energie grid area: Forecasting and planning the expansion of photovoltaics, heat pumps and charging infrastructure

The aim of this thesis is to provide a detailed forecast of the development of the expansion of photovoltaic systems, heat pumps and charging infrastructure for electric vehicles in the network area of Primeo Energie. Using socio-economic data from the Federal Statistical Office (FSO) and the Federal Office of Energy (FOE), this information is to be transferred to the network area using a grid division and the application of regionalisation factors. For the reference years 2030, 2040 and 2050, the aim is to analyse the extent to which the operating resources (transmission lines and transformers) will be utilised and at what point in time a grid expansion will be required.