Optimization of Run-of-River Hydropower Plant Design under Climate Change Conditions

Parisa Sarzaeim (), Omid Bozorg-Haddad (), Babak Zolghadr-Asli (), Elahe Fallah-Mehdipour () and Hugo A. Loáiciga ()
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Parisa Sarzaeim: University of Tehran
Omid Bozorg-Haddad: University of Tehran
Babak Zolghadr-Asli: University of Tehran
Elahe Fallah-Mehdipour: University of Tehran
Hugo A. Loáiciga: University of California

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2018, vol. 32, issue 12, No 8, 3919-3934

Abstract: Abstract The assessment of climate change and its impacts on hydropower generation is a complex issue. This paper evaluates the application of representative concentration pathways (RCPs, 2.6, 4.5, and 8.5) with the change factor (CF) method and the statistical downscaling method (SDSM) to generate six climatic scenarios of monthly temperature and rainfall over the period 2020–2049 in the Karkheh basin, Iran. The identification of unit hydrographs and component flows from rainfall, evaporation and streamflow data (IHACRES) model was employed to simulate runoff for the purpose of designing a run-of-river hydropower plant in the Karkheh basin. The non-dominated sorting genetic algorithm (NSGA)-II was employed to maximize yearly energy generation and the plant factor, simultaneously. Results indicate the runoff scenarios associated with the SDSM lead to higher run-of-river hydropower generation in 2020–2049 compared to the CF results.

Keywords: Climate change; Design; Run-of-river; Uncertainty; RCP; Change factor; Statistical downscaling model; NSGA-II (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (7)

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DOI: 10.1007/s11269-018-2027-0

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