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- Title
Estimation of Run-of-River Hydropower Potential in the Myitnge River Basin.
- Authors
Thin, Kyu Kyu; Zin, Win Win; San, Zin Mar Lar Tin; Kawasaki, Akiyuki; Moiz, Abdul; Bhagabati, Seemanta Sharma
- Abstract
The need for electricity is rapidly increasing, especially in developing countries. There is vast hydropower potential existing globally that has not yet been explored. This could be the only solution to solve future global power shortage. Hydropower is a clean and renewable source of energy because it does not exploit the use of water. However, using the conventional approach to harness hydropower results in several challenges. It is difficult to identify suitable sites and assess site potential during the planning stage of hydropower projects. In this study, run-of-river hydropower potential for the Myitnge River Basin was estimated by intergrating a Geographic Information System (GIS) and Soil & Water Assessement Tool (SWAT) model. A GIS based tool was developed using Python to spot the potential locations of the hydropower plants. The hydrological model (SWAT) was designed in order to obtain the values of monthly discharge for all potential hydropwer sites. The flow duration curves at potential locations were developed and the design discharge for hydropower was identified. Forty-four run-of-river (ROR) type potential hydropower sites were identified by considering only the topographic factors. After simulation with SWAT model, twenty potential sites with a hydropower generation potential of 292 MW were identified. Currently, only one 790 MW Yeywa Hydropower Plant, which is the largest plant in Myanmar, exists in the Myitnge River Basin. The amount of estimated power generated from ROR may increase the existing power system of Myitnge Basin by 36%. This study will assist stakeholders in the energy sector to optimize the available resources to select appropiate sites for small hydropower plants with high power potential.
- Subjects
ELECTRICITY; WATER power; GEOGRAPHIC information systems; STAKEHOLDERS; RIVERS
- Publication
Journal of Disaster Research, 2020, Vol 15, Issue 3, p267
- ISSN
1881-2473
- Publication type
Article
- DOI
10.20965/jdr.2020.p0267