Impact of Dependence on State Identification Results in Distribution Grids Using Copula Theory

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragenBegutachtung

Beitragende

Abstract

Distribution system state identification belongs to one of the most fundamental parts of modern smart grid operation strategies. The quality of identified system states is essential for subsequent algorithms. This paper deals with the impact of dependence on state identification results. Therefore, dependent data samples are generated using Copula theory with different dependence characteristics. The results of multiple Monte Carlo simulations reveal a strong influence of both degree of dependence and dependence structure on state identification errors.

Details

OriginalspracheDeutsch
TitelNEIS 2017; Conference on Sustainable Energy Supply and Energy Storage Systems
Herausgeber (Verlag)VDE Verlag, Berlin [u. a.]
Seiten1-7
Seitenumfang7
ISBN (Print)978-3-8007-4445-9
PublikationsstatusVeröffentlicht - 22 Sept. 2017
Peer-Review-StatusJa

Konferenz

TitelNEIS 2017; Conference on Sustainable Energy Supply and Energy Storage Systems
Dauer21 - 22 September 2017
OrtHamburg, Germany

Externe IDs

ORCID /0000-0001-8439-7786/work/142244131

Schlagworte