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Fortgeschrittene Technologien für die Optimierung von Stromnetzen durch das Internet der Dinge (IoT) und künstliche Intelligenz (KI)
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ISBN10: 6209038786
ISBN13: 9786209038785
Publisher: Verlag Unser Wissen
Published: Sep 28 2025
Pages: 68
Weight: 0.23
Height: 0.16 Width: 6.00 Depth: 9.00
Language: German
ISBN13: 9786209038785
Publisher: Verlag Unser Wissen
Published: Sep 28 2025
Pages: 68
Weight: 0.23
Height: 0.16 Width: 6.00 Depth: 9.00
Language: German
In dieser Arbeit wird eine Methode zur Optimierung der Leistung von Energiesystemen mithilfe des Internets der Dinge und künstlicher Intelligenz vorgestellt. Die Methode erkennt automatisch Spannungseinbrüche. Die Fehlerkorrektur erfolgt automatisch in Echtzeit durch Neukonfiguration und automatische Neukombination von Schaltern im gesamten System. Diese Technik bietet eine einfache Möglichkeit zur Überwachung von Stromnetzen mithilfe von SCADA-Geräten. Es werden Algorithmen zur adaptiven Partikelschwarmoptimierung (APSO) vorgeschlagen, um Leistungsverluste und Spannungseinbrüche (PLVD) im radialen Verteilungssystem (RDS) zu bewerten. Der IEEE 33-Bus-Standardtest wird zur Untersuchung der Netzqualität des vorgeschlagenen Systems verwendet. Anhand der Reduzierung der Verlustleistung und des Spannungsindexes werden drei geeignete Standorte für die Einspeisung von verteilten Photovoltaikquellen (PDS) ermittelt. Das System behebt Fehler wie Leistungsfaktorabweichungen (PFD) oder Teilabschattungen von Solarzellen, indem es die radialen 33-Bus-Netzzweige rekonfiguriert und automatisch wieder zusammenführt. Eine adaptive Partikelschwarmoptimierung (APSO) hat eine Verbesserung des Leistungsprofils ermöglicht und die Zuverlässigkeit der vorgeschlagenen Methode bewiesen.
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