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Make or buy : IT-based decision support for grid imbalance settlement in smarter electricity networks

DOI zum Zitieren der Version auf EPub Bayreuth:
URN to cite this document: urn:nbn:de:bvb:703-epub-7138-4

Title data

Wederhake, Lars ; Schlephorst, Simon ; Zyprian, Florian:
Make or buy : IT-based decision support for grid imbalance settlement in smarter electricity networks.
In: Energy Informatics. Vol. 5 (2022) Issue 1 . - No. 34.
ISSN 2520-8942
DOI der Verlagsversion:

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Decision (support) systems are a particularly important type of information system to energy informatics. A key challenge in energy informatics is that electricity supply must be in balance with demand at all times. More volatile renewable energy sources increase the relevance of electricity network balancing, i.e., imbalance settlement. Typically, electricity distribution network operators bought balancing power from external service providers (Buy option). Interestingly, however, more local energy resources help smarter electricity networks develop a Make option, as in our real-world evaluation. Choosing the better decision alternative within the relevant timeframes challenges human decision-making capabilities. Therefore, this research proposes a model-based decision system to improve the operators’ decisions concerning Make or Buy under various levels of data quality represented by availability, granularity, and timeliness. The study reports savings up to 40% of costs for imbalance settlement supporting ambitious development efforts by the municipality we study in our real-world evaluation.

Further data

Item Type: Article in a journal
Keywords: Decision system; Model-based decision support system; Distribution network; Data quality; Grid imbalance
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
300 Social sciences > 330 Economics
Institutions of the University: Research Institutions > Affiliated Institutes > FIM Research Center for Information Management
Research Institutions
Research Institutions > Affiliated Institutes
Language: English
Originates at UBT: Yes
URN: urn:nbn:de:bvb:703-epub-7138-4
Date Deposited: 21 Jul 2023 09:13
Last Modified: 21 Jul 2023 09:13


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