Contributors: Tim Franken, Axel Himmelberg, Marten Klein, Juan Machado, Ivan Pryvalov, Fabian Rachow, Shiva Kumar Sampangi, Johannes Staemmler, and Niklas Ziemann
AMPLIFY VOL. 37, NO. 11
Climate change will necessitate a profound transformation in economic structures, particularly global energy systems.1 This transformation is more critical in regions historically dependent on fossil fuel industries — regions that have long served as the backbone of the global energy economy.2 The imperative to change these areas from fossil-based energy production to sustainable alternatives presents a “wicked”3 challenge.
The path to structural transformation is fraught with challenges, including entrenched economic interests, technological uncertainties, social resistance, and the potential for economic disruption in communities reliant on fossil fuel industries.4 Technological change is often constrained by established systems, with high-margin incumbents reluctant to adopt low-margin, unproven alternatives, leading to a “lock-in” effect.5,6
Governments play a key role in fostering these changes, moving beyond regulatory frameworks to invest in high-risk, capital-intensive infrastructure projects and foundational research.7 The private sector must then scale these innovations for broader adoption.8
This article focuses on Lusatia, a German region historically reliant on lignite (brown coal) for energy, and its ongoing transformation under Germany’s ambitious Energiewende policy, which aims for climate neutrality by 2045. The transition involves closing all coal plants by 2038 and shifting to renewable energy. The region’s transformation is guided by the Act to Reduce and End Coal-Fired Power Generation and the Structural Development Act, which provide financial and legal frameworks to support affected regions, including Lusatia.
The German government allocated €40 billion (US $43 billion) to support the transition, which includes infrastructure projects and job creation.9 The Energy Innovation Center (EIZ) at Brandenburg University of Technology Cottbus-Senftenberg (BTU) is central to Lusatia’s transformation, supporting innovation and technology development.
EIZ: Engine of Structural Change in Lusatia
EIZ was established in 2022 to drive the regional energy transition through research, entrepreneurship, technology transfer, and collaboration with industrial partners and other research institutes in the region. It is cofinanced with up to €102 million (US $112 million) for up to 10 years by the German Federal Ministry of Education and Research (BMBF) in partnership with the Investment Bank of the State of Brandenburg.
EIZ’s Approach to Research & Innovation
The center comprises six interconnected and interdisciplinary research labs, each with a thematic focus (see Figure 1). With 15 professors, ~70 researchers and technicians at BTU, six project and innovation managers, and more than 50 additional partners from business and science, EIZ is ideally positioned for interdisciplinary research.
All EIZ research activities are dedicated to developing renewable energy technologies to replace Lusatia’s lignite-based power production system. In a complementary approach, involved labs are developing novel solutions for establishing digital, intelligent, sector-coupled, secure, socially accepted, and sustainable energy system in collaboration with ecosystem partners in the region and beyond (see Figure 2).
EIZ is dedicated to product-oriented technology development and bridging the gap between research and Industry application through open innovation concepts. To enhance this approach, EIZ SPARK was formed in 2023 to act as an innovation and entrepreneurship center, where energy researchers and students drive the transition to a sustainable energy system by creating an open innovation ecosystem that accelerates knowledge and technology transfer from the labs to the marketplace.
EIZ SPARK comprises entrepreneurs in residence and experts in energy technology, entrepreneurship, and innovation management to leverage both practical and conceptual expertise to achieve this mission. Unlike technology transfer centers that operate as independent entities across economic sectors, EIZ SPARK is closely integrated with EIZ research groups. This ensures ongoing interaction with researchers and emphasizes entrepreneurship and technology transfer.
EIZ’s generous funding for basic research and infrastructure enabled the purchase of necessary lab equipment and the hiring of approximately 70 researchers. The project also gained considerable political backing, with high-profile visits from the German president, ministers, state secretaries, and international ambassadors that elevated the project’s visibility.
The project quickly achieved significant academic success. Researchers presented their work at more than 40 global conferences and published more than 30 peer-reviewed articles within the first two years. The group participated in over 100 events, industrial fairs, and exhibitions, building partnerships with governmental and industrial organizations.
Looking to the Future: EIZ’s Technological Focus
Energy Storage & Conversion Technologies
Power-to-X-to-power energy storage systems store surplus renewable energy in chemical energy carriers and release it during periods of low renewable energy generation. These storage systems are considered carbon-free because they recirculate carbon without emitting it into the atmosphere. They play a crucial role in the large-scale integration of wind and solar power into the energy market due to their high storage capacity, resilience, and potential for sector coupling.10
The Energy Storage and Conversion (ESC) Lab focuses on understanding fundamental processes within storage systems, enhancing process integration, and reducing costs for large-scale applications. This is accomplished by a multidisciplinary research team of engineers, physicists, and chemists. Insights gained from experiments and field studies are shared with a team of computer scientists who drive the development of cutting-edge digital tools (see Figure 3).
The ESC Lab develops detailed simulation models for water electrolyzers, methane synthesis reactors, and combined heat and power plants, grounded in fundamental physical principles. These models are essential for determining fluid properties and calculating the dynamics of power-to-X-to-power energy storage systems. They enable virtual experiments that support deeper investigations and system optimization. Additionally, the data from these simulations is used to create data-driven metamodels and develop an advanced digital twin of the energy storage system.11,12
Metamodels are developed from experimental and simulation data using statistical regression and machine learning algorithms. Although these models lack a physical foundation, they “learn” physical relationships from the data used in training. They effectively balance computational speed and accuracy, making them essential for multi-criteria optimization and digital twin development.
Physical models and metamodels enable virtual optimization of real processes, allowing the ESC group to identify operating parameters that maximize efficiency, minimize energy demand, or reduce operational costs. The group develops robust, reliable optimization methods capable of handling multiple objectives and a variety of optimization parameters. Multi-criteria optimization results are validated through energy system component test benches and a power-to-X-to-power energy storage system demonstrator.13
Digital twins leverage sensor data from the energy storage system, along with data from other sources (e.g., weather forecasts and energy markets), to create a virtual representation of the system. The goal is to predict the energy storage system’s real-time behavior and provide feedback through multi-criteria decision-making. This allows the energy storage system to be automatically adjusted to changing conditions (e.g., weather, energy demand, electricity prices), ensuring optimal operation at all times.
Stochastic & Reduced-Order Models for Multi-Energy Systems
The ability to “nowcast“14 wind velocities is gaining importance as wind turbines are added to the power grid. Control is required to ascertain power grid stability so a control policy can generally benefit from more detailed knowledge of the wind velocity at a given site.
Available wind power P increases nonlinearly with the wind velocity v as P = ½ ρAv3, where ρ is the mass density of air and A is the rotor area of the wind turbine, demonstrating that accurate wind-velocity predictions are crucial for substantial improvements in the estimation of the available wind power. Based on the established correlation between power output and wind velocity, it is worth noting that wind power fluctuations can be entirely attributed to fluctuations in genuinely unsteady wind fields.
To the best of our knowledge, standalone modeling tools for atmospheric flows under variable conditions do not exist, yielding a modeling gap for the operation of next-generation energy systems.
In addition, allocation of wind power sources is generally limited by the predictive capabilities and resolution of available models. It is too costly to select a numerical weather prediction (NWP) model for wind field predictions on different time and length scales, notwithstanding that NWP data has already been used for day-ahead forecasting of wind power ramps.15 Another challenge is physically based modeling of wind-velocity profiles over a short time horizon, taking into account challenging atmospheric conditions.16
The team at the Scientific Computing Lab (SC) at EIZ explicitly addresses the challenge in wind power nowcasting for control applications, among other aspects of reduced-order modeling of multi-energy systems. It does this by developing and applying advanced stochastic tools for the standalone modeling of atmospheric wind-velocity profiles.
A one-dimensional stochastic model formulation is particularly well suited as it provides an almost ideal compromise between predictive capabilities, computational efficiency, and technical integrability.17 The innovative feature is the use of nonlinear sampling that yields intermittent turbulent fluctuations as an emerging dynamical feature that results from energy-based modeling of turbulence in the atmospheric boundary layer. These stochastic models will contribute to a secure power grid operation that accommodates volatile sources. The main goal is to develop a stochastic tool that will enable nowcasts of the available wind power at the scale of an individual wind turbine.
Monitoring & Operational Tools for Sector-Coupled Energy Systems
Accurate monitoring and robust, efficient operation of an energy system undergoing transformative changes in production, transportation, consumption, and storage require novel and cyber-secure concepts for monitoring and control.18 Future energy systems will seamlessly integrate optimally managed renewable energy assets through these advancements and accommodate new economic models for dynamic energy pricing.
This will occur in a context where demand response is prevalent and a stronger coupling exists through codesign and collaboration among various energy carriers, such as electricity and heating. Enabling these novel operating schemes is a challenging goal that requires decentralized (modular and scalable) adaptive modeling, monitoring, and cyber-secure control strategies for multi-energy systems.19
A holistic, structured, scalable approach to dynamic modeling and control has yet to be realized. Thus far, existing energy and demand management solutions are not robust enough to handle aggravating factors such as the presence of (model) uncertainties or unknown disturbances, including those originating from uncertain energy production or unpredictable fluctuating demand patterns.20 Furthermore, increasingly complex energy systems that are increasingly exposed to the Internet may become the target of cyberattacks, jeopardizing the stability of energy networks and leading to the loss of private information.21
Consequently, the main goal of the interdisciplinary Control Systems and Cyber Security (COSYS) Lab of EIZ is to provide tested, cyber-secure schemes for operating and monitoring complex sector-coupled energy systems. This includes data-centric modeling and safety assessment algorithms for networked dynamical systems.
Key objectives also include the development of methods/tools for explainable and interpretable attack and anomaly detection in digitally connected energy systems and research/evaluation of end-user privacy-protection techniques.
COSYS is also working to validate theoretical developments by commissioning a state-of-the-art hardware-in-the-loop laboratory. This facility also supports prototype testing and the demonstration of system-wide and component solutions. Such efforts are essential for promoting knowledge transfer to the region through active collaboration with local stakeholders, creating an incubation hub for new ideas, technologies, and products.
Studying the Public Acceptance of Sustainable Infrastructures
To achieve climate neutrality by 2045, Germany’s energy system must undergo significant changes, including expanding solar panels, wind parks, hydrogen infrastructure, and carbon-capture storage.22 These changes traditionally face low social acceptance, which can slow down the transformation process.23
The Energy Economics (EECON) Lab at the EIZ studies the factors influencing social acceptance of energy infrastructure projects. People from all social groups in the Lusatia area are invited to participate in a two-part study.
Participants first experience a virtual reality (VR) scenario that simulates the impact of energy infrastructure, including wind turbines, solar panels, direct reduction plants for steel decarbonization, and railway transport for carbon-capture storage. The information in the VR scenario varies between groups to analyze its effect on social acceptance. (VR is used because it creates immersion among the participants and effectively conveys information about new technologies, making them more understandable.24)
Next, participants take part in a laboratory experiment, where they make financially consequential decisions about energy infrastructure. For instance, they might decide to expand solar energy projects or provide financial support for green hydrogen projects. By focusing on consequential decisions, researchers can measure revealed preferences instead of stated preferences (the latter is hypothetical and hard to take at face value).25,26
Policymakers can use the study outcomes to accelerate the energy system transformation. For example, the results show which types of information or participation processes (procedural, financial) may be most effective in increasing public acceptance of the energy transition.
Key Insights
The focus of the EIZ on sector coupling and the intelligent digital operation/optimization of complex energy systems leads to five key insights:
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Power-to-X-to-power energy storage systems, supported by advanced simulation and digital twin technologies, enable efficient, carbon-free storage and renewable energy retrieval. Using virtual optimization and real-time system adjustments, these tools enhance storage performance, reduce operational costs, and facilitate reliable integration of renewables into the energy market.
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Advanced stochastic models for nowcasting of unsteady wind velocities offer an efficient, scalable solution for more accurately predicting wind power at individual turbine sites. These models provide means for extended predesign studies and enhanced grid stability through precise short-term forecasts that account for turbulent atmospheric fluctuations, thus contributing to improved control strategies and integration of wind energy into the power grid.
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Cyber-secure, adaptive monitoring and control tools are essential for managing and protecting complex, sector-coupled energy systems. These tools help practitioners ensure stable operations, respond to unpredictable energy demands, and defend against cyber threats, while a hardware-in-the-loop lab offers a practical environment for testing and demonstrating robust solutions in real-world scenarios.
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Engaging the public through immersive experiences like VR and using real financial decision-making scenarios can significantly improve the understanding and acceptance of energy projects. These insights can guide practitioners in designing targeted, effective communication and compensation strategies that build trust and facilitate smoother project implementation in local communities.
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Successful implementation of transformative innovation projects like the EIZ requires streamlining bureaucratic processes, enhancing funding agility, and building collaborative frameworks from the start. A specific focus must be put on reducing administrative barriers, enabling faster hiring and procurement, and fostering strong partnerships among academic, industrial, and regional stakeholders.
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