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Market Abstraction of Energy Markets and Policies - Application in an Agent-Based Modeling Toolbox

Maurer, Florian ; Miskiw, Kim K. ORCID iD icon 1; Acosta, Rebeca Ramirez; Harder, Nick; Sander, Volker; Lehnhoff, Sebastian
1 Institut für Wirtschaftsinformatik und Marketing (IISM), Karlsruher Institut für Technologie (KIT)

Abstract (englisch):

In light of emerging challenges in energy systems, markets are prone to changing dynamics and market design. Simulation models are commonly used to understand the changing dynamics of future electricity markets. However, existing market models were often created with specific use cases in mind, which limits their flexibility and usability. This can impose challenges for using a single model to compare different market designs. This paper introduces a new method of defining market designs for energy market simulations. The proposed concept makes it easy to incorporate different market designs into electricity market models by using relevant parameters derived from analyzing existing simulation tools, morphological categorization and ontologies. These parameters are then used to derive a market abstraction and integrate it into an agent-based simulation framework, allowing for a unified analysis of diverse market designs. Furthermore, we showcase the usability of integrating new types of long-term contracts and over-the-counter trading. To validate this approach, two case studies are demonstrated: a pay-as-clear market and a pay-as-bid long-term market. ... mehr


Originalveröffentlichung
DOI: 10.1007/978-3-031-48652-4_10
Dimensions
Zitationen: 1
Zugehörige Institution(en) am KIT Institut für Wirtschaftsinformatik und Marketing (IISM)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2024
Sprache Englisch
Identifikator ISBN: 978-3-031-48652-4
ISSN: 0302-9743
KITopen-ID: 1000167496
Erschienen in Energy Informatics. Ed.: B. Jørgensen. Pt. 2
Veranstaltung 3rd Energy Informatics Academy Conference (EI.A 2023), Campinas, Brasilien, 06.12.2023 – 08.12.2023
Verlag Springer Nature Switzerland
Seiten 139–157
Serie Lecture Notes in Computer Science ; 14468
Vorab online veröffentlicht am 02.12.2023
Schlagwörter energy market design, agent-based simulation, market modeling
Nachgewiesen in Dimensions
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