Machine Learning for Solar Array Monitoring, Optimization, and Control / Nejlevnější knihy
Machine Learning for Solar Array Monitoring, Optimization, and Control

Kód: 39295051

Machine Learning for Solar Array Monitoring, Optimization, and Control

Autor Sameeksha Katoch, Andreas Spanias, Gowtham Muniraju, Cihan Tepedelenlioglu, Vivek Narayanaswamy

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 mainte ... celý popis

1498


Skladem u dodavatele
Odesíláme za 8-10 dnů
Přidat mezi přání

Mohlo by se vám také líbit

Dárkový poukaz: Radost zaručena

Objednat dárkový poukazVíce informací

Více informací o knize Machine Learning for Solar Array Monitoring, Optimization, and Control

Nákupem získáte 150 bodů

Anotace knihy

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.

Parametry knihy

Zařazení knihy Knihy v němčině Naturwissenschaften, Medizin, Informatik, Technik Technik Bau- und Umwelttechnik

1498



Osobní odběr Praha, Brno a 12903 dalších

Copyright ©2008-24 nejlevnejsi-knihy.cz Všechna práva vyhrazenaSoukromíCookies


Můj účet: Přihlásit se
Všechny knihy světa na jednom místě. Navíc za skvělé ceny.

Nákupní košík ( prázdný )

Vyzvednutí v Zásilkovně
zdarma nad 1 499 Kč.

Nacházíte se: