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Application of Artificial Intelligence for the Optimization of Hydropower Energy Generation

Kumar, Krishna LU orcid and Saini, R. P. (2021) In EAI Endorsed Transactions on Industrial Networks and Intelligent Systems 8(28). p.1-12
Abstract

Hydropower is one of the most promising sources of renewable energy. However, a substantial initial investment requires for the construction of large civil structures. Feasibility study, detailed project report preparation, construction planning, and timely execution of work are the important activities of a hydropower plant. Energy generation in hydropower plants are mainly depends on discharge and head. Therefore, an accurate estimation of discharge and head is important to decide the plant capacity. Erosion, cavitation, and operation & maintenance are the key challenges in hydropower energy generation. Artificial Intelligence (AI) has become popular, which can be utilized for site selection, parameters assessment, and operation... (More)

Hydropower is one of the most promising sources of renewable energy. However, a substantial initial investment requires for the construction of large civil structures. Feasibility study, detailed project report preparation, construction planning, and timely execution of work are the important activities of a hydropower plant. Energy generation in hydropower plants are mainly depends on discharge and head. Therefore, an accurate estimation of discharge and head is important to decide the plant capacity. Erosion, cavitation, and operation & maintenance are the key challenges in hydropower energy generation. Artificial Intelligence (AI) has become popular, which can be utilized for site selection, parameters assessment, and operation & maintenance optimization. In this paper, a literature review on applications of AI in hydropower has been presented, and an attempt has also been made to identify the future potential areas of hydropower plants.

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author
and
publishing date
type
Contribution to journal
publication status
published
subject
keywords
AI, ANN, Deep Learning, Energy, Fuzzy logic, Hydropower, Machine Learning
in
EAI Endorsed Transactions on Industrial Networks and Intelligent Systems
volume
8
issue
28
pages
12 pages
publisher
European Alliance for Innovation
external identifiers
  • scopus:85117294187
ISSN
2410-0218
DOI
10.4108/EAI.6-8-2021.170560
language
English
LU publication?
no
additional info
Publisher Copyright: © 2021 Krishna Kumar et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.
id
dea24a77-3b33-4a1a-9cd2-716df635faa9
date added to LUP
2024-04-15 13:20:51
date last changed
2024-05-16 14:46:48
@article{dea24a77-3b33-4a1a-9cd2-716df635faa9,
  abstract     = {{<p>Hydropower is one of the most promising sources of renewable energy. However, a substantial initial investment requires for the construction of large civil structures. Feasibility study, detailed project report preparation, construction planning, and timely execution of work are the important activities of a hydropower plant. Energy generation in hydropower plants are mainly depends on discharge and head. Therefore, an accurate estimation of discharge and head is important to decide the plant capacity. Erosion, cavitation, and operation &amp; maintenance are the key challenges in hydropower energy generation. Artificial Intelligence (AI) has become popular, which can be utilized for site selection, parameters assessment, and operation &amp; maintenance optimization. In this paper, a literature review on applications of AI in hydropower has been presented, and an attempt has also been made to identify the future potential areas of hydropower plants.</p>}},
  author       = {{Kumar, Krishna and Saini, R. P.}},
  issn         = {{2410-0218}},
  keywords     = {{AI; ANN; Deep Learning; Energy; Fuzzy logic; Hydropower; Machine Learning}},
  language     = {{eng}},
  number       = {{28}},
  pages        = {{1--12}},
  publisher    = {{European Alliance for Innovation}},
  series       = {{EAI Endorsed Transactions on Industrial Networks and Intelligent Systems}},
  title        = {{Application of Artificial Intelligence for the Optimization of Hydropower Energy Generation}},
  url          = {{http://dx.doi.org/10.4108/EAI.6-8-2021.170560}},
  doi          = {{10.4108/EAI.6-8-2021.170560}},
  volume       = {{8}},
  year         = {{2021}},
}