Economic analysis of operation and maintenance costs of hydropower plants
(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
- Kumar, Krishna LU and Saini, R. P.
- publishing date
- 2022-10
- 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&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 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}}, }