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Englisch
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Beschreibung
This book presents novel contributions in the development of solid-state-transformer (SST) technology both for medium-voltage (MV) and low-voltage (LV) utility grid interfaces, which can potentially augment the grid modernization process in the evolving power system paradigm. For the MV interface, a single-stage AC-DC SST submodule topology has been proposed, and its modulation and soft-switching possibilities are analysed, experimentally validated and adequately benchmarked. A control scheme with power balance capability among submodules is developed for MV grid-connected single-stage AC-DC SST for smooth operation under inevitable parameter drift scenario, and experimental validation shows excellent performance under drastic load change conditions. A novel machine learning-aided multi-objective design optimization framework for grid-connected SST is developed and experimentally validated, which equips a power electronics design engineer with meagre computational resources to findout the most optimal SST design in a convenient time-frame. This book has also contributed towards the development of dual-active-bridge (DAB)-type and non-DAB-type LV grid-interfaced isolated AC-DC converters by providing solutions to specific topology and modulation-related shortcomings in these two types of topologies. A comprehensive comparison of the DAB and non-DAB-type LVAC-LVDC converters reveals the superiority of DAB-type conversion strategy.
This book presents novel contributions in the development of solid-state-transformer (SST) technology both for medium-voltage (MV) and low-voltage (LV) utility grid interfaces, which can potentially augment the grid modernization process in the evolving power system paradigm. For the MV interface, a single-stage AC-DC SST submodule topology has been proposed, and its modulation and soft-switching possibilities are analysed, experimentally validated and adequately benchmarked. A control scheme with power balance capability among submodules is developed for MV grid-connected single-stage AC-DC SST for smooth operation under inevitable parameter drift scenario, and experimental validation shows excellent performance under drastic load change conditions. A novel machine learning-aided multi-objective design optimization framework for grid-connected SST is developed and experimentally validated, which equips a power electronics design engineer with meagre computational resources to findout the most optimal SST design in a convenient time-frame. This book has also contributed towards the development of dual-active-bridge (DAB)-type and non-DAB-type LV grid-interfaced isolated AC-DC converters by providing solutions to specific topology and modulation-related shortcomings in these two types of topologies. A comprehensive comparison of the DAB and non-DAB-type LVAC-LVDC converters reveals the superiority of DAB-type conversion strategy.
Inhaltsverzeichnis
Introduction.- Selection of Submodule Topology in MVAC-LVDC Modular SST.- Half-bridge Matrix-Based Dual-Active-Bridge.- Machine Learning Aided Design Optimization Framework for Medium-Voltage Grid-Connected Solid-State-Transformers.- Power Balance Control Scheme for a Cascaded Matrix-Based Dual-Active-Bridge (CMB-DAB) Converter.- Three-Phase Matrix-Based Isolated AC-DC Conversion.- Conclusions and Future Work.
Details
| Erscheinungsjahr: | 2023 |
|---|---|
| Fachbereich: | Nachrichtentechnik |
| Genre: | Importe, Technik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| Reihe: | Springer Theses |
| Inhalt: |
xlii
263 S. 16 s/w Illustr. 122 farbige Illustr. 263 p. 138 illus. 122 illus. in color. |
| ISBN-13: | 9789811949043 |
| ISBN-10: | 9811949042 |
| Sprache: | Englisch |
| Einband: | Kartoniert / Broschiert |
| Autor: | Saha, Jaydeep |
| Hersteller: |
Springer
Springer Singapore Springer Theses |
| Verantwortliche Person für die EU: | Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com |
| Maße: | 235 x 155 x 16 mm |
| Von/Mit: | Jaydeep Saha |
| Erscheinungsdatum: | 07.11.2023 |
| Gewicht: | 0,526 kg |