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  5. Methodology for the automatic generation of optimization models of systems of flexible energy resources

Methodology for the automatic generation of optimization models of systems of flexible energy resources

Publication date
2025-01-13
Document type
Forschungsartikel
Author
Wagner, Lukas Peter  
Gehlhoff, Felix  
Reinpold, Lasse Matthias  
Frey, Georg
Jepsen, Julian  
Fay, Alexander  
Organisational unit
Automatisierungstechnik  
Angewandte Werkstofftechnik  
DTEC.bw  
DOI
10.3390/en18020325
URI
https://openhsu.ub.hsu-hh.de/handle/10.24405/20505
Project
Optimale Nutzung energetischer Flexibilitäten von Systemverbünden in der Produktion auf Basis intelligenter Agenten  
Publisher
MDPI
Series or journal
Energies
ISSN
1996-1073
Periodical volume
18
Periodical issue
2
Article ID
325
Is part of
https://openhsu.ub.hsu-hh.de/handle/10.24405/20497
Peer-reviewed
✅
Part of the university bibliography
✅
Additional Information
Language
English
Keyword
dtec.bw
Abstract
The integration of increasing shares of intermittent renewable energy necessitates flexibility in both energy generation and consumption. Typically, the operation of flexible energy resources is orchestrated through optimization models. However, the manual creation of these models is a complex and error-prone task, often requiring the expertise of domain specialists. This work introduces a methodology for the automatic generation of optimization models for systems of flexible energy resources to simplify the modeling process and increase the use of energy flexibility. This methodology utilizes a modular, generic model structure designed to depict systems of flexible energy resources. It incorporates algorithms for model parameter derivation from operational data and an information model that represents the system’s structure and dependencies of resources. The efficacy of this methodology is demonstrated in two case studies, highlighting its relevance and ability to significantly streamline the optimization modeling process by minimizing the need for manual intervention.
Description
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Version
Published version
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Metadata only access

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