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Incorporating Power Transmission Bottlenecks into Aggregated Energy System Models

Cao, Karl-Kien und Metzdorf, Johannes und Birbalta, Sinan (2018) Incorporating Power Transmission Bottlenecks into Aggregated Energy System Models. Sustainability, 10 (6). Multidisciplinary Digital Publishing Institute (MDPI). doi: 10.3390/su10061916. ISSN 2071-1050.

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Offizielle URL: http://www.mdpi.com/2071-1050/10/6/1916

Kurzfassung

Energy scenario analyses are able to provide insights into the future and possible strategies for coping with challenges such as the integration of renewable energy sources. The models used for analyzing and developing future energy systems must be simplified, e.g., due to computational constraints. Therefore, grid-related effects and regional differences are often ignored. We tackle this issue by presenting a new methodology for aggregating spatially highly resolved transmission grid information for energy system models. In particular, such approaches are required in studies that evaluate the demand for spatially balancing power generation and consumption in future energy systems. Electricity transmission between regions is crucial, especially for scenarios that rely on high shares of renewable energy sources. The presented methodology estimates transmission line congestions by evaluating the nodal price differences and then applies a spectral clustering on these particular link attributes. The objective of the proposed approach is to derive aggregated model instances that preserve information regarding electricity transmission bottlenecks. The resulting models are evaluated against observables such as the annual amount of redispatched power generation. For a selection of defined performance indicators, we find a significantly higher accuracy compared to the commonly used, spatially aggregated models applied in the field of energy scenario analysis.

elib-URL des Eintrags:https://elib.dlr.de/120656/
Dokumentart:Zeitschriftenbeitrag
Titel:Incorporating Power Transmission Bottlenecks into Aggregated Energy System Models
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Cao, Karl-KienKarl-Kien.Cao (at) dlr.dehttps://orcid.org/0000-0002-9720-0337NICHT SPEZIFIZIERT
Metzdorf, Johannesjmetzdorf (at) rocketmail.comNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Birbalta, SinanNICHT SPEZIFIZIERTNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Datum:7 Juni 2018
Erschienen in:Sustainability
Referierte Publikation:Ja
Open Access:Ja
Gold Open Access:Ja
In SCOPUS:Ja
In ISI Web of Science:Ja
Band:10
DOI:10.3390/su10061916
Verlag:Multidisciplinary Digital Publishing Institute (MDPI)
Name der Reihe:Smart Power Grid for Sustainable Energy Transition
ISSN:2071-1050
Status:veröffentlicht
Stichwörter:energy scenario; power system modeling; spectral clustering; spatial aggregation; grid and storage expansion
HGF - Forschungsbereich:Energie
HGF - Programm:TIG Technologie, Innovation und Gesellschaft
HGF - Programmthema:Erneuerbare Energie- und Materialressourcen für eine nachhaltige Zukunft
DLR - Schwerpunkt:Energie
DLR - Forschungsgebiet:E SY - Energiesystemanalyse
DLR - Teilgebiet (Projekt, Vorhaben):E - Systemanalyse und Technikbewertung (alt)
Standort: Stuttgart
Institute & Einrichtungen:Institut für Technische Thermodynamik > Systemanalyse und Technikbewertung
Hinterlegt von: Cao, Dr.-Ing. Karl-Kien
Hinterlegt am:16 Jul 2018 18:39
Letzte Änderung:08 Nov 2023 14:18

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