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How to trade electricity flexibility using artificial intelligence : An integrated algorithmic framework

Title data

Hanny, Lisa ; Körner, Marc-Fabian ; Leinauer, Christina ; Michaelis, Anne ; Strüker, Jens ; Weibelzahl, Martin ; Weissflog, Jan:
How to trade electricity flexibility using artificial intelligence : An integrated algorithmic framework.
In: Proceedings of the 55th Hawaii International Conference on System Sciences (HICSS). - Kauai, USA , 2022
ISBN 978-0-9981331-5-7

Official URL: Volltext

Abstract in another language

In course of the energy transition, the growing share of Renewable Energy Sources (RES) makes electricity generation more decentralized and intermittent. This increases the relevance of exploiting flexibility potentials that help balancing intermittent RES supply and demand and, thus, contribute to overall system resilience. Digital technologies, in the form of automated trading algorithms, may considerably contribute to flexibility exploitation, as they enablefaster and more accurate market interactions. In this paper, we develop an integrated algorithmic framework that finds an optimal trading strategy for flexibility onmultiple markets. Hence, our work supports the trading of flexibility in a multi-market environment that results in enhanced market integration and harmonization of economically traded and physically deliver edelectricity, which finally promotes resilience in highly complex electricity systems.

Further data

Item Type: Article in a book
Refereed: Yes
Keywords: Artificial Intelligence; Trading; Electricity; Flexibility; Resilience
Institutions of the University: Faculties > Faculty of Law, Business and Economics > Department of Business Administration
Faculties > Faculty of Law, Business and Economics > Department of Business Administration > Chair Business Administration XVII - Information Systems and Value-Based Business Process Management
Research Institutions
Research Institutions > Affiliated Institutes
Research Institutions > Affiliated Institutes > Fraunhofer Project Group Business and Information Systems Engineering
Research Institutions > Affiliated Institutes > FIM Research Center Finance & Information Management
Faculties
Faculties > Faculty of Law, Business and Economics
Result of work at the UBT: Yes
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
300 Social sciences > 330 Economics
Date Deposited: 04 Oct 2021 10:18
Last Modified: 31 Oct 2022 08:35
URI: https://eref.uni-bayreuth.de/id/eprint/67151