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Economic analysis of operation and maintenance costs of hydropower plants

Kumar, Krishna LU orcid and Saini, R. P. (2022) In Sustainable Energy Technologies and Assessments 53.
Abstract

The world is experiencing deep climate changes caused by increased population and rapid urbanization. Hydropower is one of the renewable energy sources that can be used to meet energy demands, but most of the hydropower plants suffer from silt erosion and cavitation problems. Therefore, it is important to decide which parts to be repair or replace, as it affects the Operation and Maintenance (O&M) costs. Presently O&M costs are speculated based on the previous years O&M costs data. Various studies are available for forecasting O&M costs, but they are plant specific. This paper deals with the assessment of the O&M costs of hydropower plants, considering the parameters and conditions involved in the O&M costs of... (More)

The world is experiencing deep climate changes caused by increased population and rapid urbanization. Hydropower is one of the renewable energy sources that can be used to meet energy demands, but most of the hydropower plants suffer from silt erosion and cavitation problems. Therefore, it is important to decide which parts to be repair or replace, as it affects the Operation and Maintenance (O&M) costs. Presently O&M costs are speculated based on the previous years O&M costs data. Various studies are available for forecasting O&M costs, but they are plant specific. This paper deals with the assessment of the O&M costs of hydropower plants, considering the parameters and conditions involved in the O&M costs of hydropower plants. The correlations are developed to predict the O&M costs of hydropower plants and found that the developed correlation models can predict the O&M costs with an accuracy having an R2-value of 0.89, Mean Absolute Percentage Error (MAPE) of 3.53% and Root Mean Square Percentage Error (RMSPE) of 4.45% for Francis turbine-based hydropower plants, and with an R2-value of 0.97, having a MAPE of 0.17% at 1.30% RMSPE for Kaplan turbine-based hydropower plants. This study may be useful for developers, plant operators, and researchers.

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author
and
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Energy, Hydropower, Operation & Maintenance, Power Plant, Turbines
in
Sustainable Energy Technologies and Assessments
volume
53
article number
102704
publisher
Elsevier
external identifiers
  • scopus:85137158639
ISSN
2213-1388
DOI
10.1016/j.seta.2022.102704
language
English
LU publication?
no
additional info
Publisher Copyright: © 2022 Elsevier Ltd
id
18a4eb7c-e1c3-4d7b-bfdb-77d29b836731
date added to LUP
2024-04-15 13:18:54
date last changed
2024-05-16 14:46:48
@article{18a4eb7c-e1c3-4d7b-bfdb-77d29b836731,
  abstract     = {{<p>The world is experiencing deep climate changes caused by increased population and rapid urbanization. Hydropower is one of the renewable energy sources that can be used to meet energy demands, but most of the hydropower plants suffer from silt erosion and cavitation problems. Therefore, it is important to decide which parts to be repair or replace, as it affects the Operation and Maintenance (O&amp;M) costs. Presently O&amp;M costs are speculated based on the previous years O&amp;M costs data. Various studies are available for forecasting O&amp;M costs, but they are plant specific. This paper deals with the assessment of the O&amp;M costs of hydropower plants, considering the parameters and conditions involved in the O&amp;M costs of hydropower plants. The correlations are developed to predict the O&amp;M costs of hydropower plants and found that the developed correlation models can predict the O&amp;M costs with an accuracy having an R<sup>2</sup>-value of 0.89, Mean Absolute Percentage Error (MAPE) of 3.53% and Root Mean Square Percentage Error (RMSPE) of 4.45% for Francis turbine-based hydropower plants, and with an R<sup>2</sup>-value of 0.97, having a MAPE of 0.17% at 1.30% RMSPE for Kaplan turbine-based hydropower plants. This study may be useful for developers, plant operators, and researchers.</p>}},
  author       = {{Kumar, Krishna and Saini, R. P.}},
  issn         = {{2213-1388}},
  keywords     = {{Energy; Hydropower; Operation & Maintenance; Power Plant; Turbines}},
  language     = {{eng}},
  publisher    = {{Elsevier}},
  series       = {{Sustainable Energy Technologies and Assessments}},
  title        = {{Economic analysis of operation and maintenance costs of hydropower plants}},
  url          = {{http://dx.doi.org/10.1016/j.seta.2022.102704}},
  doi          = {{10.1016/j.seta.2022.102704}},
  volume       = {{53}},
  year         = {{2022}},
}