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| Autore: |
Manohar Namrata
|
| Titolo: |
Machine Learning Applications in Renewable Energy / / by Namrata Manohar, Mousmi Ajay Chaurasia, Stefan Mozar, Chia-Feng Juang
|
| 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 ![]() |
| ISBN: | 9789819799398 |
| 9819799392 | |
| Formato: | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione: | Inglese |
| Record Nr.: | 9910984589603321 |
| Lo trovi qui: | Univ. Federico II |
| Opac: | Controlla la disponibilità qui |