Publikationen

2026

• Multi-Factor Stochastic Price Modeling for Battery Storage Real Option Valuation: A Framework with Peak/Offpeak Dynamics

  Heinen, A., & Epia, C. (2026). Multi-Factor Stochastic Price Modeling for Battery Storage Real Option Valuation: A Framework with Peak/Offpeak Dynamics (No. 6793078) (S. 30). http://doi.org/10.2139/ssrn.6793078 (Original work published Mai 2026)

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    • Fachbereich 2: Energy and Life Science

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  • 2026
  • Report
  • • Andreas Heinen
    • Carlos Epia

• Impact of Wind Turbulences on the Energy Yield of a Wind Turbine with a Hydraulic-Pneumatic Flywheel System in its Rotor

  Goga, A., Jauch, C., & Alhrshy, L. (2026). Impact of Wind Turbulences on the Energy Yield of a Wind Turbine with a Hydraulic-Pneumatic Flywheel System in its Rotor. In NEIS Conference 2025 (S. 170–177). Hamburg: VDE Verlag GmbH. http://doi.org/10.30420/566633024 (Original work published März 2026)

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  Wind turbulence introduces variations and oscillations in the power output of wind turbines and vibrations of wind turbine components. Higher turbulence intensities lead to significant wind speed fluctuations, necessitating frequent aerodynamic regulation of the rotor in near-rated operating points. Reducing these fluctuations stabilizes the operation of the wind turbine, which reduces power fluctuations in the grid, and which reduces wear and tear in the wind turbine. This study investigates a hydraulic-pneumatic flywheel system designed to leverage these fluctuations by absorbing excess energy during gusts (charging) and releasing it during lulls (discharging), effectively smoothing the power output. The charging phase of this system introduces an additional electrical load by driving hydraulic pumps with electric motors, thereby increasing the generator torque. Simultaneously, fluid movement along the rotor blades induces Coriolis forces, generating a negative torque that slows down the rotor. This flywheel system application reduces rotor speed and pitch angle excursions during peak wind events by storing surplus energy. When the wind speeds drop below rated wind speed due to turbulence, the stored energy is released by transferring the fluid from the tip accumulators to storage tanks in the blade roots, reducing the flywheel inertia, and hence, releasing energy. This bidirectional functionality allows mitigating the downsides of turbulence. The objective of this study is to assess the performance of the flywheel system in stabilizing power output and to quantify the energy yield improvement, with a particular focus on the influence of turbulence intensity.

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    • Goga, Abhinay
    • Jauch, Clemens
    • Alhrshy, Laurence

  • Forschungsprojekt

    • Ressourceneffizienz in der Windenergie

  • Abteilung/Einrichtung

    • Wind Energy Technology Institute

  • Profilbereich

    • Erneuerbare Energien und nachhaltige Entwicklung

  • Forschungsfeld

    • Wind

  • Fachbereich

    • Fachbereich 2: Energy and Life Science

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  • 2026
  • Conference Paper
  • • Abhinay Goga
    • Prof. Dr. Clemens Jauch
    • Laurence Alhrshy
  • • Wind Turbine
    • Variable inertia flywheel
    • Energy yield
    • Turbulence intensity

• Physik - Ausgewählte Grundkonzepte für Natur- und Ingenieurwissenschaften

  Vest, A., & Voigt, A. (2026). Physik - Ausgewählte Grundkonzepte für Natur- und Ingenieurwissenschaften (S. 436). Hamburg: Books on Demand GmbH. Abgerufen von https://buchshop.bod.de/physik-alexander-voigt-9783819275401

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    • Vest, Anja

  • Fachbereich

    • Fachbereich 2: Energy and Life Science

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  • 2026
  • Book
  • • Anja Vest
    • Alexander Voigt
  • • Physik

• On Wind Directions Estimated by Nacelle Lidar Under Different Reconstruction Methods

  Guo, F., Xu, W., Zhang, Z., Schlipf, D., Schito, P., Zasso, A., … Dong, Y. (2026). On Wind Directions Estimated by Nacelle Lidar Under Different Reconstruction Methods. Wind Energy, 29, e70098. http://doi.org/10.1002/we.70098

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    • Schlipf, David

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  • 2026
  • Journal Article
  • • Feng Guo
    • Wenhao Xu
    • Zhaoyu Zhang
    • David Schlipf
    • Paolo Schito
    • Alberto Zasso
    • Zhen Gao
    • Yujin Dong

• Benchmarking Foundation Models for Mitotic Figure Classification

  Ammeling, J., Ganz, J., Rosbach, E., Lausser, L., Bertram, C. A., Breininger, K., & Aubreville, M. (2026). Benchmarking Foundation Models for Mitotic Figure Classification. Machine Learning for Biomedical Imaging, 3, 38–58. http://doi.org/"https://doi.org/10.59275/j.melba.2026-a3eb"

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  • Personenseiten

    • Aubreville, Marc

  • Forschungsprojekt

    • (mu)ROMI: Robust and Accurate Multi-Tumor, Multi-Species, Multi-Laboratory and Multi-Scanner Mitosis Detection with Large-Scale Datasets and Artificial Intelligence

  • Abteilung/Einrichtung

    • FLAIR - Flensburg Artificial Intelligence Research

  • Profilbereich

    • Gesundheit und Life Sciences

  • Forschungsfeld

    • Data Science und Künstliche Intelligenz

  • Fachbereich

    • Fachbereich 3: Information und Kommunikation

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  • 2026
  • Journal Article
  • • Jonas Ammeling
    • Jonathan Ganz
    • Emely Rosbach
    • Ludwig Lausser
    • Christof Bertram
    • Katharina Breininger
    • Marc Aubreville

• Exploring General-purpose Autonomous Multimodal Agents for Pathology Report Generation

  Aubreville, M., Donovan, T. A., & Bertram, C. A. (2026). Exploring General-purpose Autonomous Multimodal Agents for Pathology Report Generation. In H. Handels, K. Breininger, T. Deserno, A. Maier, K. Maier-Hein, C. Palm, & T. Tolxdorff (Hrsg.), Bildverarbeitung für die Medizin 2026 (S. 393–399). Wiesbaden: Springer Fachmedien Wiesbaden. http://doi.org/10.1007/978-3-658-51100-5_76

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    • Aubreville, Marc

  • Forschungsprojekt

    • (mu)ROMI: Robust and Accurate Multi-Tumor, Multi-Species, Multi-Laboratory and Multi-Scanner Mitosis Detection with Large-Scale Datasets and Artificial Intelligence

  • Abteilung/Einrichtung

    • FLAIR - Flensburg Artificial Intelligence Research

  • Forschungsfeld

    • Data Science und Künstliche Intelligenz

  • Fachbereich

    • Fachbereich 3: Information und Kommunikation

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  • 2026
  • Conference Paper
  • • Marc Aubreville
    • Taryn Donovan
    • Christof Bertram
    • Heinz Handels
    • Katharina Breininger
    • Thomas Deserno
    • Andreas Maier
    • Klaus Maier-Hein
    • Christoph Palm
    • Thomas Tolxdorff

• A method for validating loads and responses of large floating wind turbines using nacelle-mounted lidar

  Guo, F., Schlipf, D., & Gao, Z. (2026). A method for validating loads and responses of large floating wind turbines using nacelle-mounted lidar. Marine Structures, 108, 104019. http://doi.org/10.1016/j.marstruc.2026.104019

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    • Schlipf, David

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  • 2026
  • Journal Article
  • • Feng Guo
    • David Schlipf
    • Zhen Gao

• Enabling Fast and Mobile Histopathology Image Annotation through Swipeable Interfaces SWAN

  Banerjee, S., Gosch, T., Hester, S., Weiss, V., Conrad, T., Donovan, T. A., … Aubreville, M. (2026). Enabling Fast and Mobile Histopathology Image Annotation through Swipeable Interfaces SWAN. In H. Handels, K. Breininger, T. Deserno, A. Maier, K. Maier-Hein, C. Palm, & T. Tolxdorff (Hrsg.), Bildverarbeitung für die Medizin 2026 (S. 203–209). Wiesbaden: Springer Fachmedien Wiesbaden. http://doi.org/10.1007/978-3-658-51100-5_42

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    • Banerjee, Sweta
    • Porsche, Nils
    • Aubreville, Marc

  • Forschungsprojekt

    • (mu)ROMI: Robust and Accurate Multi-Tumor, Multi-Species, Multi-Laboratory and Multi-Scanner Mitosis Detection with Large-Scale Datasets and Artificial Intelligence

  • Abteilung/Einrichtung

    • FLAIR - Flensburg Artificial Intelligence Research

  • Profilbereich

    • Informatik und Gestaltung

  • Forschungsfeld

    • Data Science und Künstliche Intelligenz

  • Fachbereich

    • Fachbereich 3: Information und Kommunikation

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  • 2026
  • Conference Paper
  • • Sweta Banerjee
    • Timo Gosch
    • Sara Hester
    • Viktoria Weiss
    • Thomas Conrad
    • Taryn Donovan
    • Nils Porsche
    • Jonas Ammeling
    • Christoph Stroblberger
    • Robert Klopfleisch
    • Christopher Kaltenecker
    • Christof Bertram
    • Katharina Breininger
    • Marc Aubreville
    • Heinz Handels
    • Thomas Deserno
    • Andreas Maier
    • Klaus Maier-Hein
    • Christoph Palm
    • Thomas Tolxdorff

• Optimisation of the Hydraulic Variable Inertia Flywheel for Specific Energy

  Rettig, A., Reese, L., & Jauch, C. (2026). Optimisation of the Hydraulic Variable Inertia Flywheel for Specific Energy. In 19. Symposium Energieinnovation 2026. Östereich, Graz. http://doi.org/https://doi.org/10.13140/RG.2.2.10150.59203

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  The ongoing transition towards inverter-based generation is significantly reducing conventional rotational inertia in power systems, leading to increased rates of change of frequency. To address this challenge, the Hydraulic Variable Inertia Flywheel (HVI-FW) represents a novel alternative for distributed and inherent inertia provision. This paper presents a design tool developed to optimize the geometric parameters of the novel flywheel, with respect to specific energy. A parameter study is conducted by varying key geometric dimensions, such as radius and height. The results demonstrate that the HVI-FW can achieve significantly higher specific energy than conventional flywheels, particularly for small radii, making it well suited for coupling with small, synchronously rotating electrical machines. The findings highlight the potential of the HVI-FW as an effective solution for providing distributed inertia in future low-inertia power systems.

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  • Personenseiten

    • Jauch, Clemens

  • Forschungsprojekt

    • Inno!Nord-HYDRAD - Hydraulischer Schwungradspeicher

  • Abteilung/Einrichtung

    • Wind Energy Technology Institute

  • Profilbereich

    • Erneuerbare Energien und nachhaltige Entwicklung

  • Forschungsfeld

    • Netzintegration

  • Fachbereich

    • Fachbereich 2: Energy and Life Science

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  • 2026
  • Conference Paper
  • • Arne Rettig
    • Lisanne Reese
    • Prof. Dr. Clemens Jauch
  • • Flywheel, Inertia, Power System Inertia, Energy Storage, Electrical Machines

• Evaluation of ChatGPT Study Mode: Results from an Expert Rating Regarding Self-Regulated Learning

  Steinberg, E., Perels, F., Aubreville, M., & Dörrenbächer-Ulrich, L. (2026). Evaluation of ChatGPT Study Mode: Results from an Expert Rating Regarding Self-Regulated Learning. Open Education Studies, 8, 20250169. http://doi.org/10.1515/edu-2025-0169

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  • Personenseiten

    • Aubreville, Marc

  • Abteilung/Einrichtung

    • CIVU – Center for Interaction, Visualization and Usability
    • FLAIR - Flensburg Artificial Intelligence Research

  • Fachbereich

    • Fachbereich 3: Information und Kommunikation

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  • 2026
  • Journal Article
  • • Evelyn Steinberg
    • Franziska Perels
    • Marc Aubreville
    • Laura Dörrenbächer-Ulrich