Optimization of renewable energy sources using emerging computational techniques
Kumar, Aman ; Kumar, Krishna LU
and Kapoor, Nishant Raj
(2022)
p.187-236
- Abstract
Energy is essential for the sustenance of life. The energy and economy of any nation are interlinked—energy demand is generally proportional to the economic growth of the nation. In the present era, renewable energy (RE) is the primary area of interest to save fossil fuels, achieve sustainability, and reducing carbon emissions, as well as other gases in the atmosphere that create climatic problems. The abundance of wind, sunlight, tidal, geothermal heat, and other renewable resources on Earth must be used appropriately for the welfare of Homo sapiens and for securing the environment and other living beings. For the past few years, the area of research in the RE sector has grown day by day. Advanced computational technologies are used in... (More)
Energy is essential for the sustenance of life. The energy and economy of any nation are interlinked—energy demand is generally proportional to the economic growth of the nation. In the present era, renewable energy (RE) is the primary area of interest to save fossil fuels, achieve sustainability, and reducing carbon emissions, as well as other gases in the atmosphere that create climatic problems. The abundance of wind, sunlight, tidal, geothermal heat, and other renewable resources on Earth must be used appropriately for the welfare of Homo sapiens and for securing the environment and other living beings. For the past few years, the area of research in the RE sector has grown day by day. Advanced computational technologies are used in data optimization. This chapter mainly focuses on all types of RE sources and electricity generation statistical data from the foremost countries adopting RE generation technologies.
(Less)
- author
- Kumar, Aman
; Kumar, Krishna
LU
and Kapoor, Nishant Raj
- publishing date
- 2022-01-01
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- AMPE, Artificial intelligence, Bioenergy, Energy, Renewable energy, RMSE
- host publication
- Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies
- pages
- 50 pages
- publisher
- ScienceDirect, Elsevier
- external identifiers
-
- scopus:85137473314
- ISBN
- 9780323912280
- 9780323914284
- DOI
- 10.1016/B978-0-323-91228-0.00012-4
- language
- English
- LU publication?
- no
- additional info
- Publisher Copyright: © 2022 Elsevier Inc. All rights reserved.
- id
- 46fa478b-e3dd-45bf-9c66-060cf5aee0de
- date added to LUP
- 2024-04-15 13:28:53
- date last changed
- 2024-06-10 19:22:42
@inbook{46fa478b-e3dd-45bf-9c66-060cf5aee0de,
abstract = {{<p>Energy is essential for the sustenance of life. The energy and economy of any nation are interlinked—energy demand is generally proportional to the economic growth of the nation. In the present era, renewable energy (RE) is the primary area of interest to save fossil fuels, achieve sustainability, and reducing carbon emissions, as well as other gases in the atmosphere that create climatic problems. The abundance of wind, sunlight, tidal, geothermal heat, and other renewable resources on Earth must be used appropriately for the welfare of Homo sapiens and for securing the environment and other living beings. For the past few years, the area of research in the RE sector has grown day by day. Advanced computational technologies are used in data optimization. This chapter mainly focuses on all types of RE sources and electricity generation statistical data from the foremost countries adopting RE generation technologies.</p>}},
author = {{Kumar, Aman and Kumar, Krishna and Kapoor, Nishant Raj}},
booktitle = {{Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies}},
isbn = {{9780323912280}},
keywords = {{AMPE; Artificial intelligence; Bioenergy; Energy; Renewable energy; RMSE}},
language = {{eng}},
month = {{01}},
pages = {{187--236}},
publisher = {{ScienceDirect, Elsevier}},
title = {{Optimization of renewable energy sources using emerging computational techniques}},
url = {{http://dx.doi.org/10.1016/B978-0-323-91228-0.00012-4}},
doi = {{10.1016/B978-0-323-91228-0.00012-4}},
year = {{2022}},
}