Identifying high potential locations for run-of-the-river hydroelectric power plants using GIS and digital elevation models

Arjumand Z. Zaidi, Majid Khan

Research output: Contribution to journalReview articlepeer-review

32 Scopus citations

Abstract

The recent global energy crisis has provoked a need to explore alternate energy sources including run-of-the-river hydropower projects. To derive maximum payback for a given investment, finding the most advantageous siting of power plants is imperative. If a selection of potential sites misses some of the apparently indistinct sites with significant power potential, there is a chance of acquiring only partial benefits out of these investments. A review of the existing methods for evaluating power potential of a river is discussed in this paper with their limitations along with a new proposed approach. The new approach can be used to evaluate different installation schemes along a river to assess run-of-the-river hydropower potentials using geospatial data techniques to select sites exhibiting higher total hydropower potential. The case study of Kunhar River, located in the northern part of Pakistan, presents the applicability of the approach. Open source Advanced Spaceborne Thermal Emission (ASTER)’s digital elevation model (DEM) and regional hydrologic gauged data are used for identifying the best locations for hydropower plants, demonstrating this approach is substantially more cost effective and robust compared to other field based assessment. Replicating the proposed approach for other locations is easy following the step-by-step method presented in this paper and giving consideration to the limitations described. This study may provide guidelines for the development of cost-effective and energy efficient hydropower projects. The use of this approach is most advantageous in the preliminary assessment phase of a project to narrow the scope of the detailed study focusing only on the higher potential sites.

Original languageEnglish
Pages (from-to)106-116
Number of pages11
JournalRenewable and Sustainable Energy Reviews
Volume89
DOIs
StatePublished - Jun 2018
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Energy
  • Geospatial
  • GIS
  • Hydropower potential
  • Remote sensing
  • Run-of-the-river

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