Ravelijn

dr. D. Guericke MSc (Daniela)

Assistant Professor
BMS-HBE-IEBIS
Ravelijn 3355
d.guericke@utwente.nl
+31534899791
Business card

Daniela Guericke is Assistant Professor for Stochastic Operations Research at the Section Industrial Engineering and Business Information Systems. Her research focuses sustainable operations by utilizing (stochastic) operations research and optimization methods in application areas such as energy systems and health care. In particular,  she is interested in decision-making under uncertainty and solving large-scale optimization problems.

Daniela received her PhD in Business Information Systems from the Decision Support and Operations Research Lab, Paderborn University. Afterwards,  she worked as a postdoctoral researcher at the Department of Applied Mathematics and Computer Science, Technical University of Denmark (DTU). In 2020, she became Assistant Professor for Decision-making under Uncertainty in Integrated Energy Systems at DTU. In 2021, Daniela received the Young Researchers Award of the German OR Society (GOR e.V.).

Expertise

  • Computer Science

    • Models
    • Control
    • Design

  • Engineering

    • District Heating System
    • Energy Engineering
    • Optimization
    • Networks
    • Planning

Organisations

Publications

2024

A memetic NSGA-II for the multi-objective flexible job shop scheduling problem with real-time energy tariffs (2024)Flexible services and manufacturing journal, 36, 1530-1570. Burmeister, S. C., Guericke, D. & Schryen, G.https://doi.org/10.1007/s10696-023-09517-7Correction: A memetic NSGA‑II for the multi‑objective flexible job shop scheduling problem with real‑time energy tariffs (2024)Flexible services and manufacturing journal, 36, 1571-1573. Burmeister, S. C., Guericke, D. & Schryen, G.https://doi.org/10.1007/s10696-023-09530-wA Stochastic Investment Planning Model for On-Site Energy Sector Coupling in Data Centers (2024)[Working paper › Preprint]. Social Science Research Network (SSRN). Guericke, D., Dominković, D. F. & Junker, R. G.https://doi.org/10.2139/ssrn.5005870A generic stochastic network-based formulation for production optimization of district heating systems (2024)Energy Systems (E-pub ahead of print/First online). Guericke, D., Schledorn, A. & Madsen, H.https://doi.org/10.1007/s12667-024-00698-0Frigg 2.0: Integrating price-based demand response into large-scale energy system analysis (2024)Applied energy, 364. Article 122960. Schledorn, A., Charousset-Brignol, S., Junker, R. G., Guericke, D., Madsen, H. & Dominković, D. F.https://doi.org/10.1016/j.apenergy.2024.122960

2023

Frigg 2.0: Integrating Price-Based Demand Response into Large-Scale Energy System Analysis (2023)[Working paper › Preprint]. Social Science Research Network (SSRN). Schledorn, A., Charousset-Brignol, S., Junker, R. G., Guericke, D., Madsen, H. & Dominković, D. F.https://doi.org/10.2139/ssrn.4617554Can occupant behaviors affect urban energy planning? Distributed stochastic optimization for energy communities (2023)Applied energy, 348. Article 121589. Leprince, J., Schledorn, A., Guericke, D., Dominkovic, D. F., Madsen, H. & Zeiler, W.https://doi.org/10.1016/j.apenergy.2023.121589Optimizing planning and operation of renewable energy communities with genetic algorithms (2023)Applied energy, 338. Article 120906. Lazzari, F., Mor, G., Cipriano, J., Solsona, F., Chemisana, D. & Guericke, D.https://doi.org/10.1016/j.apenergy.2023.120906Can occupant behaviors affect urban energy planning? Distributed stochastic optimization for energy communities (2023)[Working paper › Preprint]. Leprince, J., Schledorn, A., Guericke, D., Dominkovic, D. F., Madsen, H. & Zeiler, W.

2022

A generic stochastic network flow formulation for production optimization of district heating systems (2022)[Working paper › Preprint]. Guericke, D., Schledorn, A. & Madsen, H.

Research profiles

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