Jelke Wibbeke, Master of Science (M.Sc.) Senior Researcher

Master of Science (M.Sc.) Jelke Wibbeke
Kontaktdaten
Tätigkeiten

Position im OFFIS

Senior Researcher

Forschungsbereiche

Energie / Vertrauenswürdiger Systembetrieb

Forschungsinteresse

Data-Centric Machine Learning, Imbalanced Regression, Digital Twins for Energy and Industrial Systems
News

+49 441 9722-492

jelke.wibbeke(at)offis.de

Publikationen
von Jelke Wibbeke, Master of Science (M.Sc.)

2025

Co-Simulation and MAS Approach for Assessment of Large-Scale Electrolysers Potential in Flexibility Markets

Sharaf Alsharif, Danila Valko, Jelke Wibbeke and Sebastian Lehnhoff; IEEE PowerTech 2025; 2025

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2024

Co-Simulation Analysis for Large-Scale Electrolysers Integration in Electricity Grids

Sharaf Alsharif, Danila Valko, Nils Huxoll, Jelke Wibbeke, Tobias Grimm and Michael Brand; European Simulation and Modelling Conference 2024 (ESM 2024); October / 2024

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Digital Twin concept and architecture for fleets of hydrogen electrolysers

Sharaf Alsharif, Nils Huxoll, Jelke Wibbeke, Tobias Grimm, Michael Brand, Sebastian Lehnhoff; Frontiers in Energy Efficiency; 07 / 2024

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Poster Abstract: A Digital Twin Platform Applied to Hydrogen Electrolyzers

Amit Kumar Singh, Jelke Wibbeke, Amin Raeiszahdeh, Nils Huxoll, Michael Brand; DACH+ Conference on Energy Informatics 2024; October / 2024

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2023

Estimating time-delayed variables using transformer-based soft sensors

Jelke Wibbeke, Darian Alves, Sebastian Rohjans; Energy Informatics; 10 / 2023

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2022

Optimal Data Reduction of Training Data in Machine Learning-Based Modelling: A Multidimensional Bin Packing Approach

Jelke Wibbeke, Payam Teimourzadeh Baboli, Sebastian Rohjans; Energies ; Jan. / 2022

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2021

Power Systems Digital Twin under Measurement and Model Uncertainties: Network Parameter Tuning Approach

Jelke Wibbeke, Mohannad Aldebs, Davood Babazadeh, Payam Teimourzadeh Baboli, Sebastian Lehnhoff; 2021 IEEE Madrid PowerTech; 2021

URL DOI BIB