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Sizing of Small Hydropower Plants for Highly Variable Flows in Tropical Run-of-River Installations: A Case Study of the Sebeya River

Author

Listed:
  • Geoffrey Gasore

    (African Center of Excellence in Energy for Sustainable Development, University of Rwanda, Avenue de l’ Armée, Kigali P.O. Box 3900, Rwanda)

  • Arthur Santos

    (Energy Institute, Colorado State University, 430 N. College Avenue, Fort Collins, CO 80524, USA)

  • Etienne Ntagwirumugara

    (African Center of Excellence in Energy for Sustainable Development, University of Rwanda, Avenue de l’ Armée, Kigali P.O. Box 3900, Rwanda)

  • Daniel Zimmerle

    (Energy Institute, Colorado State University, 430 N. College Avenue, Fort Collins, CO 80524, USA)

Abstract

Rivers in tropical climates are characterized by highly variable flows which are becoming more variable due to climate change. In tropical conditions, most hydropower plants are designed as run-of-river plants with limited water storage. The aim of this study is the selection and sizing of a hydropower plant for highly variable flows, using the Sebeya River as a case study. As is often the case, flow data was incomplete, and the study also demonstrated the use of machine learning to predict the Sebeya flow rate for 2019. Stochastic modeling was used to estimate the energy generation for multiple turbine types and the levelized cost of energy for all configurations, capturing the uncertainty in many of the input parameters. River flow varies between 1.3 m 3 /s and 5.5 m 3 /s in a year; the minimum LCOE occurs at the knee in the flow exceedance curve of river flow rate, near 1.8 m 3 /s. The optimal LCOE for the Sebeya river is around 0.08 $/kwh with an uncertainty of −0.011/+0.009 $/kWh. Additionally, certain turbine types—notably propeller turbines—perform poorly in this type of highly variable flow. The method and findings can be used to guide future investments in small- to mid-sized hydropower plants in similar climatic conditions.

Suggested Citation

  • Geoffrey Gasore & Arthur Santos & Etienne Ntagwirumugara & Daniel Zimmerle, 2023. "Sizing of Small Hydropower Plants for Highly Variable Flows in Tropical Run-of-River Installations: A Case Study of the Sebeya River," Energies, MDPI, vol. 16(3), pages 1-14, January.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:3:p:1304-:d:1047297
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    References listed on IDEAS

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    1. Ouyang, Xiaoling & Lin, Boqiang, 2014. "Levelized cost of electricity (LCOE) of renewable energies and required subsidies in China," Energy Policy, Elsevier, vol. 70(C), pages 64-73.
    2. Jaewon Jung & Heechan Han & Kyunghun Kim & Hung Soo Kim, 2021. "Machine Learning-Based Small Hydropower Potential Prediction under Climate Change," Energies, MDPI, vol. 14(12), pages 1-10, June.
    3. Geoffrey Gasore & Helene Ahlborg & Etienne Ntagwirumugara & Daniel Zimmerle, 2021. "Progress for On-Grid Renewable Energy Systems: Identification of Sustainability Factors for Small-Scale Hydropower in Rwanda," Energies, MDPI, vol. 14(4), pages 1-16, February.
    4. Aggidis, G.A. & Luchinskaya, E. & Rothschild, R. & Howard, D.C., 2010. "The costs of small-scale hydro power production: Impact on the development of existing potential," Renewable Energy, Elsevier, vol. 35(12), pages 2632-2638.
    5. Epari Ritesh Patro & Teegala Srinivasa Kishore & Ali Torabi Haghighi, 2022. "Levelized Cost of Electricity Generation by Small Hydropower Projects under Clean Development Mechanism in India," Energies, MDPI, vol. 15(4), pages 1-16, February.
    6. Shaojun Yang & Hua Wei & Le Zhang & Shengchao Qin, 2021. "Daily Power Generation Forecasting Method for a Group of Small Hydropower Stations Considering the Spatial and Temporal Distribution of Precipitation—South China Case Study," Energies, MDPI, vol. 14(15), pages 1-19, July.
    7. Singh, Vineet Kumar & Singal, S.K., 2017. "Operation of hydro power plants-a review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 610-619.
    8. Michelle Sapitang & Wanie M. Ridwan & Khairul Faizal Kushiar & Ali Najah Ahmed & Ahmed El-Shafie, 2020. "Machine Learning Application in Reservoir Water Level Forecasting for Sustainable Hydropower Generation Strategy," Sustainability, MDPI, vol. 12(15), pages 1-19, July.
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