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Record Nr. |
UNINA9910864185203321 |
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Autore |
Pierfederici Serge |
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Titolo |
Electrimacs 2022 : Selected Papers - Volume 2 |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing AG, , 2024 |
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©2024 |
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ISBN |
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Edizione |
[1st ed.] |
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Descrizione fisica |
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1 online resource (322 pages) |
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Collana |
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Lecture Notes in Electrical Engineering Series ; ; v.1164 |
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Altri autori (Persone) |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Intro -- Preface to Electrimacs 2022, Volume 2 -- Contents -- Part I Modelling and Computational Simulation for Energy Systems -- 1 Efficiency Maps of Synchronous Machines Based on Electrical Circuits Modelling -- 1.1 Introduction -- 1.2 Efficiency Maps (EM) as a Predesign Tool -- 1.3 Synchronous Machines Models -- 1.3.1 Per-Unit System -- 1.4 Efficiency Maps Computation -- 1.4.1 Non-salient Poles Machines -- 1.4.2 Salient Poles Machines -- 1.5 Tool Validation -- 1.6 Tool Exploitation -- 1.6.1 PM Synchronous Machines -- 1.6.2 Synchronous Reluctance Machines -- 1.7 Conclusions -- References -- 2 Losses Prediction in the Frequency Domain for Voltage Source Inverters -- 2.1 Introduction -- 2.2 Theoretical Modelling -- 2.2.1 Passives Losses Model -- 2.2.2 Current Harmonics Calculation from Laplace Transform -- 2.2.3 AC Side Inductor Equivalent Impedance Characterisation and Modelling -- 2.2.4 Active Losses -- 2.3 Expérimental Validation -- 2.3.1 Test Conditions -- 2.3.2 Calculation of Current Harmonics from Laplace Transform for Both ZVS and HS Operating Modes -- 2.3.3 Commutations Losses for Hard-Switching -- 2.3.4 AC Side Inductor Equivalent Series Resistance Modelling -- 2.3.5 Passives Losses Model -- 2.4 Conclusion -- References -- 3 Online Detection of PV Degradation Effects Through ANNClassifier -- 3.1 Introduction -- 3.2 System Description -- 3.2.1 Model Based Approach for Identifying the PV Degradation -- 3.2.2 Generation of Degraded I-V Curves Dataset -- 3.3 FDD Implementation on Pynq-Z2 Platform -- 3.3.1 SDM Parameters Identification Tool -- 3.3.2 MLP Classifier -- 3.4 |
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