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Perturbation-Based Load Sensitivity Identification for Solid-State Transformer-Based Load Control

Courcelle, Maëva ORCID iD icon 1; Tao, Qiucen ORCID iD icon 1; Geis-Schroer, Johanna ORCID iD icon 2; Leibfried, Thomas 2; De Carne, Giovanni ORCID iD icon 1
1 Institut für Technische Physik (ITEP), Karlsruher Institut für Technologie (KIT)
2 Institut für Elektroenergiesysteme und Hochspannungstechnik (IEH), Karlsruher Institut für Technologie (KIT)

Abstract (englisch):

In recent years, the electricity supply has become more volatile, and advanced real-time controllers are needed to manage the grid safely. Demand-side management represents a promising solution, where regulating load consumption through controlled voltage variations offers a valuable approach, which can be applied using power electronics actuators. This approach relies on understanding how power consumption reacts to changes in voltage magnitude or frequency. One proposed method is perturbation-based load sensitivity identification, which introduces controlled perturbation into the grid, for instance through a Solid-State Transformer, and calculates load parameters via power measurements. However, existing methods often require synchronization with the perturbation actuator and lack resiliency to noise or uncorrelated power variations, limiting their practical applicability. This paper proposes a novel approach for perturbation-based load sensitivity identification, utilizing a pre- and post-filtering process. This method has been tested under realistic grid conditions, with autonomous computation of the load sensitivity, triggered by variation-based perturbation detection. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000174034
Veröffentlicht am 09.09.2024
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Elektroenergiesysteme und Hochspannungstechnik (IEH)
Institut für Technische Physik (ITEP)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2024
Sprache Englisch
Identifikator ISSN: 0885-8977, 1937-4208
KITopen-ID: 1000174034
HGF-Programm 37.12.03 (POF IV, LK 01) Smart Areas and Research Platforms
Erschienen in IEEE Transactions on Power Delivery
Verlag Institute of Electrical and Electronics Engineers (IEEE)
Seiten 1–12
Projektinformation HGF, HGF IVF2016 TALENT, VH-NG-1613
Nachgewiesen in Dimensions
Scopus
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