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Abstract

Hydropower plants are among the most efficient and reliable renewable energy systems in the world as far as electricity production is concerned. Run-of-river hydropower plants seem more attractive than conventional hydroelectric plants since they can be a cheaper and environmentally friendly alternative. However, their expected energy production pattern heavily depends on several construction variables that need an appropriate design using specific models. This paper analyzes several existing models used for the calculation of the diameter and thickness of a penstock, the optimal selection and implantation (admissible suction head) of a turbine, to estimate the energy produced and expected cost of small hydropower projects for grid-connected and off-grid/micro-grid applications. This review particularly brings out the specificities of each of the models to suggest the most appropriate model according to the context of study and proposes methods to use them more efficiently. This review can be used as a guide in the design and simulation of run-of-river hydropower plants, thus helping in the assessment of the economic feasibility of projects that usually requires a high level of experience and expertise.

Highlights

A critical review focused particularly on run-of-river hydropower plant design models was carried out.

Several calculation models including diameter and thickness of a penstock, admissible suction head of a turbine, and cost and energy production estimation for grid-connected applications are collected and analyzed.

Hydropower models for design and generation profile prediction presented can be used to optimally come against the variability problem of run-of river plants.

The paper can be used as a guide in the design and simulation of run-of-river hydropower plants with appropriate models.

Details

Title
Design models for small run-of-river hydropower plants: a review
Pages
3
Publication year
2023
Publication date
Dec 2023
Publisher
Springer Nature B.V.
e-ISSN
2198994X
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2890354907
Copyright
Copyright Springer Nature B.V. Dec 2023