Machine learning solar array par rao sunil (11 résultats)
Machine Learning for Solar Array Monitoring, Optimization, and Control (Synthesis Lectures on Power Electronics)
Rao, Sunil; Katoch, Sameeksha; Narayanaswamy, Vivek; Muniraju, Gowtham; Tepedelenlioglu, Cihan; Spanias, Andreas
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Vendeur : AHA-BUCH GmbH, Einbeck, AllemagneAHA-BUCH GmbH
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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - The efficiency of solar energy farms requires detailed analytics and information on each panel regarding voltage, current, temperature, and irradiance. Monitoring utility-scale solar arrays was shown to minimize the cost of maintenance and help optimiz…e the performance of the photo-voltaic arrays under various conditions. We describe a project that includes development of machine learning and signal processing algorithms along with a solar array testbed for the purpose of PV monitoring and control. The 18kW PV array testbed consists of 104 panels fitted with smart monitoring devices. Each of these devices embeds sensors, wireless transceivers, and relays that enable continuous monitoring, fault detection, and real-time connection topology changes. The facility enables networked data exchanges via the use of wireless data sharing with servers, fusion and control centers, and mobile devices. We develop machine learning and neural network algorithms for fault classification. In addition, we use weather camera data for cloud movement prediction using kernel regression techniques which serves as the input that guides topology reconfiguration. Camera and satellite sensing of skyline features as well as parameter sensing at each panel provides information for fault detection and power output optimization using topology reconfiguration achieved using programmable actuators (relays) in the SMDs. More specifically, a custom neural network algorithm guides the selection among four standardized topologies. Accuracy in fault detection is demonstrate at the level of 90+% and topology optimization provides increase in power by as much as 16% under shading.
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Vendeur : preigu, Osnabrück, Allemagnepreigu
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Taschenbuch. Etat : Neu. Machine Learning for Solar Array Monitoring, Optimization, and Control | Sunil Rao (u. a.) | Taschenbuch | Synthesis Lectures on Power Electronics | ix | Englisch | 2020 | Springer | EAN 9783031013775 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[…dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Machine Learning for Solar Array Monitoring, Optimization, and Control (Synthesis Lectures on Engineering, Science, and Technology)
Rao, Sunil; Katoch, Sameeksha; Narayanaswamy, Vivek; Muniraju, Gowtham; Tepedelenlioglu, Cihan
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Vendeur : BOOKWEST, Phoenix, AZ, Etats-UnisBOOKWEST
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Hardcover. Etat : New. US SELLER SHIPS FAST FROM USA.
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Vendeur : Brook Bookstore On Demand, Napoli, NA, ItalieBrook Bookstore On Demand
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Etat : new. Questo è un articolo print on demand.
Machine Learning for Solar Array Monitoring, Optim
Rao, Sunil; Katoch, Sameeksha; Narayanaswamy, Vivek; Muniraju, Gowtham; Tepedelenlioglu, Cihan; Spanias, Andreas
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Vendeur : Basi6 International, Irving, TX, Etats-UnisBasi6 International
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Etat : Brand New. New. US edition. Print on demand title. Delivery takes 20-25 days.
Langue : anglais
Edité par Springer International Publishing Aug 2020, 2020
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AllemagneBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The efficiency of solar energy farms requires detailed analytics and information on each panel regarding voltage, current, temperature, and irradiance. Monitoring utility-scale solar arrays was shown to minimize the cost of maintenance…and help optimize the performance of the photo-voltaic arrays under various conditions. We describe a project that includes development of machine learning and signal processing algorithms along with a solar array testbed for the purpose of PV monitoring and control. The 18kW PV array testbed consists of 104 panels fitted with smart monitoring devices. Each of these devices embeds sensors, wireless transceivers, and relays that enable continuous monitoring, fault detection, and real-time connection topology changes. The facility enables networked data exchanges via the use of wireless data sharing with servers, fusion and control centers, and mobile devices. We develop machine learning and neural network algorithms for fault classification. In addition, we use weather camera data for cloud movement prediction using kernel regression techniques which serves as the input that guides topology reconfiguration. Camera and satellite sensing of skyline features as well as parameter sensing at each panel provides information for fault detection and power output optimization using topology reconfiguration achieved using programmable actuators (relays) in the SMDs. More specifically, a custom neural network algorithm guides the selection among four standardized topologies. Accuracy in fault detection is demonstrate at the level of 90+% and topology optimization provides increase in power by as much as 16% under shading. 92 pp. Englisch.
Machine Learning for Solar Array Monitoring, Optimization, and Control (Synthesis Lectures on Power Electronics)
Rao, Sunil; Katoch, Sameeksha; Narayanaswamy, Vivek; Muniraju, Gowtham; Tepedelenlioglu, Cihan; Spanias, Andreas
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Vendeur : Majestic Books, Hounslow, Royaume-UniMajestic Books
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Etat : New. Print on Demand.
Machine Learning for Solar Array Monitoring, Optimization, and Control (Synthesis Lectures on Power Electronics)
Rao, Sunil; Katoch, Sameeksha; Narayanaswamy, Vivek; Muniraju, Gowtham; Tepedelenlioglu, Cihan; Spanias, Andreas
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Vendeur : Biblios, frankfurt am main, HESSE, AllemagneBiblios
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Vendeur : moluna, Greven, Allemagnemoluna
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The efficiency of solar energy farms requires detailed analytics and information on each panel regarding voltage, current, temperature, and irradiance. Monitoring utility-scale solar arrays was shown to minimize the cost…of maintenance and help optimize the.
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Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagnebuchversandmimpf2000
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EUR 56,70
EUR 60,00 expéditionExpédition depuis Allemagne vers Etats-UnisQuantité disponible : 1 disponible(s)
Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -The efficiency of solar energy farms requires detailed analytics and information on each panel regarding voltage, current, temperature, and irradiance. Monitoring utility-scale solar arrays was shown to minimize the cost of maintenance and…help optimize the performance of the photo-voltaic arrays under various conditions. We describe a project that includes development of machine learning and signal processing algorithms along with a solar array testbed for the purpose of PV monitoring and control. The 18kW PV array testbed consists of 104 panels fitted with smart monitoring devices. Each of these devices embeds sensors, wireless transceivers, and relays that enable continuous monitoring, fault detection, and real-time connection topology changes. The facility enables networked data exchanges via the use of wireless data sharing with servers, fusion and control centers, and mobile devices. We develop machine learning and neural network algorithms for fault classification. In addition, we use weather camera data for cloud movement prediction using kernel regression techniques which serves as the input that guides topology reconfiguration. Camera and satellite sensing of skyline features as well as parameter sensing at each panel provides information for fault detection and power output optimization using topology reconfiguration achieved using programmable actuators (relays) in the SMDs. More specifically, a custom neural network algorithm guides the selection among four standardized topologies. Accuracy in fault detection is demonstrate at the level of 90+% and topology optimization provides increase in power by as much as 16% under shading.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 92 pp. Englisch.
