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Evaluation of Temporal Complexity Reduction Techniques Applied to Storage Expansion Planning in Power System Models

Raventós, Oriol und Bartels, Julian (2020) Evaluation of Temporal Complexity Reduction Techniques Applied to Storage Expansion Planning in Power System Models. Energies, 13 (4). Multidisciplinary Digital Publishing Institute (MDPI). doi: 10.3390/en13040988. ISSN 1996-1073.

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Offizielle URL: http://dx.doi.org/10.3390/en13040988

Kurzfassung

The growing share of renewable energy makes the optimization of power flows in power system models computationally more complicated, due to the widely distributed weather-dependent electricity generation. This article evaluates two methods to reduce the temporal complexity of a power transmission grid model with storage expansion planning. The goal of the reduction techniques is to accelerate the computation of the linear optimal power flow of the grid model. This is achieved by choosing a small number of representative time periods to represent one whole year. To select representative time periods, a hierarchical clustering is used to aggregate either adjacent hours chronologically or independently distributed coupling days into clusters of time series. The aggregation efficiency is evaluated by means of the error of the objective value and the computational time reduction. Further, both the influence of the network size and the efficiency of parallel computation in the optimization process are analysed. As a test case, the transmission grid of the northernmost German federal state of Schleswig-Holstein with a scenario corresponding to the year 2035 is considered. The considered scenario is characterized by a high share of installed renewables.

elib-URL des Eintrags:https://elib.dlr.de/134223/
Dokumentart:Zeitschriftenbeitrag
Titel:Evaluation of Temporal Complexity Reduction Techniques Applied to Storage Expansion Planning in Power System Models
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Raventós, OriolOriol.RaventosMorera (at) dlr.dehttps://orcid.org/0000-0002-0512-4331NICHT SPEZIFIZIERT
Bartels, JulianJulian.Bartels (at) dlr.dehttps://orcid.org/0000-0002-2623-9787NICHT SPEZIFIZIERT
Datum:22 Februar 2020
Erschienen in:Energies
Referierte Publikation:Ja
Open Access:Ja
Gold Open Access:Ja
In SCOPUS:Ja
In ISI Web of Science:Ja
Band:13
DOI:10.3390/en13040988
Verlag:Multidisciplinary Digital Publishing Institute (MDPI)
ISSN:1996-1073
Status:veröffentlicht
Stichwörter:power system modeling; energy system modeling; renewable energy; linear optimal power flow; time series aggregation; storage capacity expansion planning
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: Oldenburg
Institute & Einrichtungen:Institut für Vernetzte Energiesysteme > Energiesystemanalyse
Hinterlegt von: Raventos Morera, Dr. Oriol
Hinterlegt am:24 Mär 2020 15:26
Letzte Änderung:25 Okt 2023 08:17

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