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Advanced Technologies in Power Grids Optimization using IoT and AI: Energy efficiency using the Internet of Things and the Artificial Intelligence - Brossura
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Advanced Technologies in Power Grids Optimization using IoT and AI
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PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000. Codice articolo L2-9786208456733
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Advanced Technologies in Power Grids Optimization using IoT and AI
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PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000. Codice articolo L2-9786208456733
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Advanced Technologies in Power Grids Optimization using IoT and AI
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LAP Lambert Academic Publishing, 2025
ISBN 10: 6208456738
ISBN 13: 9786208456733
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Da: California Books, Miami, FL, U.S.A.
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Advanced Technologies in Power Grids Optimization using IoT and AI
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LAP LAMBERT Academic Publishing Sep 2025, 2025
ISBN 10: 6208456738
ISBN 13: 9786208456733
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 72 pp. Englisch. Codice articolo 9786208456733
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Advanced Technologies in Power Grids Optimization using IoT and AI : Energy efficiency using the Internet of Things and the Artificial Intelligence
Editore:
LAP LAMBERT Academic Publishing, 2025
ISBN 10: 6208456738
ISBN 13: 9786208456733
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Da: AHA-BUCH GmbH, Einbeck, Germania
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This work presents a method for optimizing the performance of energy systems using the Internet of Things and artificial intelligence. The method automatically detects voltage dips. Fault correction is performed automatically in real time by reconfiguring and automatically recombining switches across the entire system. This technique provides an easy way to supervise power networks using SCADA devices. Adaptive particle swarm optimization (APSO) algorithms are proposed to evaluate power losses and voltage dips (PLVD) on the radial distribution system (RDS). The IEEE 33 bus standard test is used to study the power quality of the proposed system. Three suitable locations for the injection of photovoltaic distributed sources (PDS) are determined based on the reduction in power loss and the voltage index. The system rectifies faults such as power factor deviation (PFD) or partial shading of solar cells by reconfiguring and automatically recombining the 33-bus radial system branches. An Adaptive particle swarm optimization (APSO) has enabled the power profile to be improved and demonstrated the reliability of the proposed method. Codice articolo 9786208456733
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Advanced Technologies in Power Grids Optimization using IoT and AI
Editore:
LAP Lambert Academic Publishing, 2025
ISBN 10: 6208456738
ISBN 13: 9786208456733
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Advanced Technologies in Power Grids Optimization using IoT and AI
Editore:
LAP Lambert Academic Publishing, 2025
ISBN 10: 6208456738
ISBN 13: 9786208456733
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Advanced Technologies in Power Grids Optimization using IoT and AI
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LAP Lambert Academic Publishing, 2025
ISBN 10: 6208456738
ISBN 13: 9786208456733
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Da: Biblios, Frankfurt am main, HESSE, Germania
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Condizione: New. PRINT ON DEMAND. Codice articolo 18405276092
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Advanced Technologies in Power Grids Optimization using IoT and AI (Paperback)
Editore:
LAP Lambert Academic Publishing, 2025
ISBN 10: 6208456738
ISBN 13: 9786208456733
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Da: CitiRetail, Stevenage, Regno Unito
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Paperback. Condizione: new. Paperback. This work presents a method for optimizing the performance of energy systems using the Internet of Things and artificial intelligence. The method automatically detects voltage dips. Fault correction is performed automatically in real time by reconfiguring and automatically recombining switches across the entire system. This technique provides an easy way to supervise power networks using SCADA devices. Adaptive particle swarm optimization (APSO) algorithms are proposed to evaluate power losses and voltage dips (PLVD) on the radial distribution system (RDS). The IEEE 33 bus standard test is used to study the power quality of the proposed system. Three suitable locations for the injection of photovoltaic distributed sources (PDS) are determined based on the reduction in power loss and the voltage index. The system rectifies faults such as power factor deviation (PFD) or partial shading of solar cells by reconfiguring and automatically recombining the 33-bus radial system branches. An Adaptive particle swarm optimization (APSO) has enabled the power profile to be improved and demonstrated the reliability of the proposed method. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Codice articolo 9786208456733
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Advanced Technologies in Power Grids Optimization using IoT and AI
Editore:
LAP LAMBERT Academic Publishing Sep 2025, 2025
ISBN 10: 6208456738
ISBN 13: 9786208456733
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Taschenbuch
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This work presents a method for optimizing the performance of energy systems using the Internet of Things and artificial intelligence. The method automatically detects voltage dips. Fault correction is performed automatically in real time by reconfiguring and automatically recombining switches across the entire system. This technique provides an easy way to supervise power networks using SCADA devices. Adaptive particle swarm optimization (APSO) algorithms are proposed to evaluate power losses and voltage dips (PLVD) on the radial distribution system (RDS). The IEEE 33 bus standard test is used to study the power quality of the proposed system. Three suitable locations for the injection of photovoltaic distributed sources (PDS) are determined based on the reduction in power loss and the voltage index. The system rectifies faults such as power factor deviation (PFD) or partial shading of solar cells by reconfiguring and automatically recombining the 33-bus radial system branches. An Adaptive particle swarm optimization (APSO) has enabled the power profile to be improved and demonstrated the reliability of the proposed method.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 72 pp. Englisch. Codice articolo 9786208456733
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