Energy system-oriented identification of hydrogen storage supply scenarios: method development and application within the Digi-HyPro Project

Publication date
2024-12-20
Document type
Sammelbandbeitrag oder Buchkapitel
Author
Lange, Jelto
Kaltschmitt, Martin
Wildner, Lukas
Reininghaus, Nies
Pistoor, Astrid
Muñoz Robinson, Carlos
Kröner, Michael
Dyck, Alexander
Organisational unit
DOI
URI
Project
Publisher
UB HSU
Book title
dtec.bw-Beiträge der Helmut-Schmidt-Universität / Universität der Bundeswehr Hamburg : Forschungsaktivitäten im Zentrum für Digitalisierungs- und Technologieforschung der Bundeswehr dtec.bw : Band 2 – 2024
ISBN
First page
30
Last page
35
Is part of
Peer-reviewed
✅
Part of the university bibliography
✅
Files
Language
English
Keyword
dtec.bw
Energy and hydrogen storage
Energy system modelling and optimization
Operational scenarios
Technology development
Abstract
Effective hydrogen storage is vital for the widespread adoption of hydrogen in energy systems, as it enables flexibility across various sectors. However, assessing such energy storage systems' suitability in future energy system configurations presents several challenges. One such challenge is the identification of representative operational scenarios for experimental testing of storage systems. Against this background, this paper presents an approach to derive such operational scenarios with the help of energy system modelling and optimization. Using the open-source energy system model and data set of Europe, PyPSA-Eur, cost-optimal future energy system configurations are identified, allowing the derivation of operational scenarios for energy storage facilities from the operation of the overall energy system. For this purpose, the methodology provides a way to identify a representative storage system from the entirety of corresponding storages in the energy system. Further, it allows determining representative time series sections using a segment identification algorithm, providing a basis for experimental technology testing. For an exemplary application of this methodology, further post-processing is implemented to consider the feasibility limits of subsystem components. The results showcase the effectiveness of the approach, offering a transparent and reproducible framework for defining operational scenarios for storage testing aligned with future energy system requirements.
Version
Published version
Access right on openHSU
Open access