Podrobná bibliografia
| Názov: |
Design and Development of Crossflow Turbine for Off-Grid Electrification. |
| Autori: |
Tesfay, Asfafaw H., Weldemariam, Sirak A., Gebrelibanos, Kalekiristos G. |
| Zdroj: |
Energies (19961073); Oct2025, Vol. 18 Issue 19, p5108, 18p |
| Predmety: |
TURBINES, DISTRIBUTED power generation, RESOURCE management, WATER power, CAPACITY building |
| Geografický termín: |
ETHIOPIA |
| Abstrakt: |
Investing in large-scale hydropower is on the rise in Ethiopia in accordance with the country's climate-resilient green economy strategy. Rural electrification is a top priority on the development agenda of the country, with very limited off-grid interventions. Although small-scale hydropower can bring various social and economic benefits compared to other off-grid solutions, it is hardly localized in the country. The motivation for this research is to break this technological bottleneck by synergizing and strengthening the local capacity. Accordingly, this paper presents the full-scale crossflow turbine design and development process of a power plant constructed to give electricity access to about 450 households in a rural village called Amentila. Based on a site survey and the resource potential, the power plant was designed for a 125 kW peak at 0.3 m3/s of discharge with a 53 m head. The crossflow was selected based on the head, discharge, and simplicity of development with the available local capacities. The detailed design of the turbine and its auxiliary components was developed and simulated using SolidWorks and CFD ANSYS CFX. The power plant has a run-of-river design, targeting provision of power during peak hours. This study demonstrates an off-grid engineering solution with applied research on the water–energy–food–environment nexus. [ABSTRACT FROM AUTHOR] |
|
Copyright of Energies (19961073) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Databáza: |
Complementary Index |