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A systematic decision support tool for robust hydropower site selection in poorly gauged basins

Abdul Moiz, Akiyuki Kawasaki, Toshio Koike and Maheswor Shrestha

Applied Energy, 2018, vol. 224, issue C, 309-321

Abstract: The power output of run-of-river small hydropower (SHP) developments is very site sensitive and poses several complex challenges, such as inaccessible terrain and numerous possible hydropower scheme alternatives. We developed a geographic information system-based decision support tool that systematically evaluates all possible hydropower scheme alternatives to assist decision makers in assessing the hydropower potential of large data-scarce regions more objectively. A water and energy budget – based distributed hydrological model and a preference ranking organization method for enrichment evaluations are integrated and employed in the developed tool. This approach enables the inclusion of both topographical and hydrological factors in the site selection process, allowing the use of hydropower potential as a maximizing criterion during site selection. This paper explores the consideration of topographical factors with and without hydrological factors as approaches for optimized site selection. An application of the tool in the case of Kunhar River Basin in Pakistan demonstrates its robustness. For equivalent criteria weights, site selection considering both factors identified a significantly lower number of sites with a shorter waterway length compared to when only topographic factors were considered. However, both approaches identified essentially the same hydropower potential. Notably, the integration with a distributed hydrological model and the incorporation of hydropower potential as a maximizing criterion for site selection revealed more economically attractive SHP sites. This approach enables a flexible and rigorous evaluation of the hydropower potential of large poorly gauged basins, which is particularly useful for developing countries.

Keywords: Decision support; Run-of-river; Site selection; Distributed hydrological model (search for similar items in EconPapers)
Date: 2018
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