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Machine Learning Applications in Renewable Energy / / by Namrata Manohar, Mousmi Ajay Chaurasia, Stefan Mozar, Chia-Feng Juang



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Autore: Manohar Namrata Visualizza persona
Titolo: Machine Learning Applications in Renewable Energy / / by Namrata Manohar, Mousmi Ajay Chaurasia, Stefan Mozar, Chia-Feng Juang Visualizza cluster
Pubblicazione: Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025
Edizione: 1st ed. 2025.
Descrizione fisica: 1 online resource (263 pages)
Disciplina: 006.31
Soggetto topico: Machine learning
Renewable energy sources
Energy policy
Machine Learning
Renewable Energy
Energy Policy, Economics and Management
Aprenentatge automàtic
Energies renovables
Política energètica
Soggetto genere / forma: Llibres electrònics
Altri autori: ChaurasiaMousmi Ajay  
MozarStefan  
JuangChia-Feng  
Nota di contenuto: 1. Renewable Energy Technologies (RET) – Society and Government Perspective -- 2. Waste-to-Energy (wte) -- 3. Computation of Energy from Waste -- 4. Grid Integration of Renewable Energy System(gires) -- 5. Artificial Intelligence and IOT in Renewable Energy.
Sommario/riassunto: This book presents the need for Renewable Energy Technologies (RET) in the context of providing a solution for the depletion of conventional resources, protecting the environment and enhancing the economic situation of a country by way of providing employment opportunities for many people may be as employees in various roles or initiating their own enterprise. The book includes statistics on energy consumption changes over the past few decades from conventional to renewable energies. The future scenario of energy in view of technological advancements and the employment status past, present and future is indicated. The need and importance of standards for the efficient operation of renewable energy systems are explained. The various modern technologies that are enabling the successful implementation of RET are presented. The role of the public and government and the various financial schemes governments provide is highlighted. A few modern applications and those under development would enhance the standard of living. The statistics and situation of the various aspects in the wake of the COVID-19 pandemic before, during and future effects are discussed, for the overall benefit of one and all. The various methods of a cost analysis of a project are indicated. Solar system components and the cost estimation of the solar power system in the present-day market status are provided. The various grid integration issues have been discussed.
Titolo autorizzato: Machine Learning Applications in Renewable Energy  Visualizza cluster
ISBN: 9789819799398
9819799392
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910984589603321
Lo trovi qui: Univ. Federico II
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Serie: Green Energy and Technology, . 1865-3537