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

被引：0
作者：
Parisa Sarzaeim
Omid Bozorg-Haddad
Babak Zolghadr-Asli
Elahe Fallah-Mehdipour
Hugo A. Loáiciga
机构：
[1] University of Tehran,Department of Irrigation & Reclamation Engineering, Faculty of Agriculture Engineering & Technology, College of Agriculture & Natural Resources
[2] National Elites Foundation,Department of Geography
[3] University of California,undefined
来源：
Water Resources Management | 2018年 / 32卷
关键词：
Climate change; Design; Run-of-river; Uncertainty; RCP; Change factor; Statistical downscaling model; NSGA-II;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
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.
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页码：3919 / 3934
页数：15
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