The reliable operation of transmission systems is one of the key challenges in today’s energy transition. In the control rooms of transmission system operators (TSOs), real-time decisions must be made to keep the power system stable and secure. A growing focus lies on forecasting methods that enable operators to anticipate the future state of the grid as precisely as possible. One central aspect is congestion management: predicting when and where bottlenecks will occur and designing measures to resolve them effectively.

Due to the increasing complexity and volatility of the system, classical approaches are often extended by modern, data-driven methods. Machine learning plays an important role in improving forecasts of demand, generation, and grid load, thereby supporting operators in real-time decision-making. These approaches combine system knowledge with advanced analytics, opening up new possibilities for research and application in system operation.

Students with an interest in energy system operation, forecasting, congestion management, or the application of machine learning in the power system context are invited to explore these topics further.

If you are interested in writing a bachelor’s or master’s thesis on this topic, please get in touch with Ms. Klara Krkalović.

Ancillary services refer to essential functions that ensure the secure and stable operation of the power grid. Particularly important in this context is the provision of balancing services, which guarantee that generation and consumption remain in balance at all times and that grid frequency is stabilized within permissible limits.

The energy transition introduces new challenges for the planning and organization of these services. The growing share of photovoltaic, wind, and battery storage systems, as well as the increasing electrification of industry and mobility, are fundamentally changing the structure of generation and consumption. These developments require adjustments both in the balancing markets and in the technical implementation of grid control.

In my research, I focus on identifying risks in the procurement of ancillary services in a fully renewable energy system and on developing solutions to address these challenges. Key areas of my work include:

• the functioning of balancing markets and their interactions with other electricity markets,
• the technical design of grid control (e.g., voltage/frequency control) and the impacts of new forms of generation and consumption, such as altered inertia or the use of battery storage as balancing resources,
• the implications of alternative methods for providing ancillary services, such as through photovoltaic and wind power plants, battery storage, controllable consumers, or aggregators.

For inquiries regarding bachelor’s or master’s theses on this topic, please contact Tobias Steiner.

The study of power system stability comprises a set of analyses carried out to evaluate the ability of an electric power system, under specific operating conditions, to return to equilibrium after being subjected to disturbances. Assessing the system’s stability status is of essential importance, since for secure operation, power systems must be capable of withstanding a wide range of disturbances.

In conventional power systems, stability issues are mainly classified into three categories: rotor angle stability, frequency stability, and voltage stability. With the transition toward power-electronics-based generation, two additional categories have been added to this classification: resonance stability and converter-driven stability.

For inquiries regarding bachelor’s or master’s theses on this subject area, please contact Mr Javad Rezaei.

My supervision of master’s and bachelor’s students focuses on energy management and optimization in advanced energy systems, including microgrids and energy communities. Building on control theory and machine learning techniques, we develop innovative strategies to improve efficiency, reliability, and resilience in these decentralized networks.

Students engage with real-world challenges such as dynamic load balancing, renewable integration, and predictive maintenance. They apply methods like model predictive control, reinforcement learning, and optimization frameworks to minimize energy losses and maximize resource utilization.

Through hands-on projects and simulations, mentees gain practical experience in designing intelligent, adaptive systems that drive the transition toward a greener energy future. Along the way, they acquire interdisciplinary skills at the intersection of engineering, data science, and environmental stewardship.

For inquiries regarding bachelor’s or master’s theses on this topic, please contact Dr. Ibrahim Brahmia.

Grid operators play an important role in making the energy transition possible by keeping the power system running safely. As electricity demand grows and more decentralized renewable energy is added, grid usage is increasing much faster than grid expansion. This creates challenges for secure operation, for example when too much solar power leads to overloads.

This makes congestion management necessary in the distribution grids as well, not least because most renewable energy systems, such as PV systems, are connected to the medium- and low-voltage grid. In Austria, redispatch is currently only carried out by the transmission system operator. Here, the limit for the feed-in capacity is to be lowered from over ten MW to over one MW, and renewable energy systems are to be included. This could result in five times as many generation plants being integrated into the redispatch process. In the future, this limit is expected to drop below one MW, which could lead to a data volume of up to half a million.

Looking ahead, introducing redispatch in distribution networks (known in Germany as "Redispatch 2.0") will also require new ways of managing flexibility. In addition, forecasts for distribution grids, possible upgrades to existing transmission capacity, and the consumption behavior of end users will all need to be considered.

If you are interested in writing a bachelor’s or master’s thesis on this topic, please get in touch with Ms. Katharina Kastberger.

Development and refinement of power system models to support grid planning, analysis, and optimization. This includes grid modeling and simulations, as well as studies of load flows, short circuits, grid stability, and failure scenarios. In addition, system services (e.g., ancillary services such as balancing power) in the transmission grid are modeled and analyzed to evaluate and further develop system-supporting methods and tools.

For inquiries regarding bachelor’s or master’s theses on this topic, please contact Dr. Thomas Kaufmann.

The operation of the interconnected power system is becoming increasingly complex. Past incidents have highlighted how crucial the resilience of the energy system is for its secure operation. This level of security must be ensured both during and after the completion of the energy transition.

Under-Frequency Load Shedding (UFLS) is an important system protection concept designed to prevent blackouts in the event of severe disturbances with significant generation deficits. However, the increasing integration of decentralized generation units poses major challenges to current approaches and reduces the available UFLS potential (no longer purely load-based feeders). At the same time, the decommissioning of fossil power plants decreases overall system inertia, leading to faster frequency dynamics and more severe frequency disturbances.

Up to now, UFLS dimensioning has been based on annual average load values and a stepwise response to frequency drops. In practice, however, load conditions vary significantly throughout the day, seasonally, and across different years. As a result, in the event of a disturbance, the available shedding capacity can deviate considerably from the required values—either too much or too little.

Therefore, adaptive UFLS concepts need to be developed to enable a more accurate determination of the amount of load to be shed and an optimal selection of shedding points. This ensures that as few feeders as possible are disconnected, while still providing an effective system response.

For inquiries regarding bachelor’s or master’s theses on this topic, please contact Marbod Kollnig.

In the planning of transmission and distribution grids, scenario techniques are used to create accurate models of future grid operation in order to identify the need for expansion and reinforcement measures at an early stage. Increasingly, so-called mass simulations—automated analyses of many grid usage cases—are applied. In addition to established planning studies, these allow probabilistic assessments of bottlenecks, operational challenges, and potential future risks. With grid operation becoming ever more volatile due to the growing integration of renewable generation, such approaches are becoming increasingly important at all grid levels. Moreover, new practical questions continue to arise, requiring solutions based on scientific methods.

Starting from the highest voltage levels, HVDC (High Voltage Direct Current) and FACTS (Flexible AC Transmission Systems) are becoming economically and technically feasible planning options. These technologies provide new opportunities for grid planning—initially at the top level, and in the future also at medium voltage levels. They enable more efficient grid utilization not only by influencing grid impedances, but also through active and controllable management of active and reactive power flows. This makes it possible to integrate larger shares of renewable energy within the same grid structures. Such technologies can positively influence grid behavior across all time scales, both under normal and disturbed operating conditions, and are being modeled and studied in various research projects at the institute.

Adequacy, or generation-load balance, is becoming an increasingly important aspect of operational planning across all time horizons (from several years ahead to day-ahead) in the context of the energy transition. At its core, the challenge is how to ensure that generation and consumption are reliably matched at all times in the future. Public discussions often refer to terms such as “Dunkelflaute” (extended periods of low renewable generation) or “Hellbrise” (periods of high renewable generation), but these reduce the broader scientific challenges to just two isolated aspects. At the institute, practical questions concerning future system operation and adequacy are addressed using scientific methods, based on both real-world experience and projections of renewable development.

For inquiries regarding bachelor’s or master’s theses on this topic, please contact Prof. Dr. Bernd Klöckl.