Artikel

A dynamic partitioning method for power system parallel restoration considering restoration-related uncertainties

Online Decision Support System (DSS) for restorative control can be used to track the restoration process of power system dynamically and optimize the restoration plans online to support the decision-making of dispatchers' online restorative control. Parallel restoration can improve the restoration efficiency effectively, but the division of the restoration partitions should match the real-time conditions of the power grid. This paper proposes a dynamic partitioning method for power system restoration considering the restoration capabilities of partitions, which can be used to refresh the partitioning results dynamically based on the power system restoration process so as to cope with the restoration-related uncertainties. Furthermore, the restoration targets (outage power plants and outage substations) of partitions will be filtered and evaluated based on its restoration values to maximize the overall restoration revenues. A decision support system for restorative control is developed and a case study using data of a real regional grid in China is conducted to illustrate the flexibility and effectiveness of the proposed method in dealing with restoration-related uncertainties.

Sprache
Englisch

Erschienen in
Journal: Energy Reports ; ISSN: 2352-4847 ; Volume: 6 ; Year: 2020 ; Issue: 2 ; Pages: 352-361 ; Amsterdam: Elsevier

Klassifikation
Wirtschaft
Thema
Decision support system
Dynamic partitioning
Parallel restoration
Restorative control

Ereignis
Geistige Schöpfung
(wer)
Li, Ze
Xue, Yusheng
Wang, Haohao
Hao, Lili
Ereignis
Veröffentlichung
(wer)
Elsevier
(wo)
Amsterdam
(wann)
2020

DOI
doi:10.1016/j.egyr.2019.11.087
Handle
Letzte Aktualisierung
10.03.2025, 11:42 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Artikel

Beteiligte

  • Li, Ze
  • Xue, Yusheng
  • Wang, Haohao
  • Hao, Lili
  • Elsevier

Entstanden

  • 2020

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