Identification of run-of-river hydropower investments in data scarce regions using global data

The increase in economic activities, population and rural electrification has significantly increased the energy demand in most of the developing nations. This demand has to be supplied from various sources, preferably renewable, among which hydropower is expected to be one of the major contributors. Though developed nations have already harnessed most of their hydropower potential, developing nations are still struggling in project identification and capacity assessment, mainly due to lack of data and difficulties of access. We present and test an assessment framework, developed for data scarce regions, to identify optimal location and installed capacity of multiple run-of-river hydropower projects within a river basin. The developed framework consists of two components: the first component is a hydrological model for flow duration curves, the second component is a so-called hydropower model. Flow duration curves are obtained using an existing probabilistic hydrological model which derives the probability distribution of streamflow as a function of few topographic and climatic parameters. A novel optimization procedure is developed, where viable hydropower projects are identified minimizing their specific cost, which depends mainly on discharge, head and length of conduit system. We tested the assessment framework in the West Rapti basin (Nepal). The application showed that the total potential of this basin maybe achieved with 79 different projects with capacity ranging from 1 to 17 MW. The framework was developed using open languages and software and can therefore be freely used after request to the corresponding author. (C) 2020 International Energy Initiative. Published by Elsevier Inc. All rights reserved.