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Developing Optimal Reservoir Rule Curve for Hydropower Reservoir with an add-on Water Supply Function Using Improved Grey Wolf Optimizer

Author

Listed:
  • Youngje Choi

    (Korea Institute of Civil Engineering and Building Technology)

  • Jungwon Ji

    (Ajou University)

  • Eunkyung Lee

    (Ajou University)

  • Sunmi Lee

    (Ajou University)

  • Sooyeon Yi

    (University of California)

  • Jaeeung Yi

    (Ajou University)

Abstract

Climate change affects water demand and supply and causes more severe droughts and floods. To meet the increasing water demand and to prepare for the exacerbating climate change-fueled droughts, the South Korean government added a water supply function to the Hwacheon reservoir, built initially as a hydropower reservoir. However, it is missing the reservoir rule curve for water supply. The main objective is to develop a rule curve that maximizes water supply reliability and the operating objective of the Hwacheon reservoir. We develop the rule curve with a well-known optimization technique (Genetic Algorithms (GA)) and new optimization techniques (Grey Wolf Optimizer (GWO) and Improved Grey Wolf Optimizer (IGWO)). The novelty of this study is developing the most appropriate rule curve for hydropower reservoir with add-on water supply function. We evaluate and compare the performance of the developed rule curve to the firm supply method (FSM). We use the discrete hedging rule to build rule curve that provides a scheduled and rationing supply. The performance indices are time-based reliability, volumetric reliability, and the number of months when the reservoir storage is in each storage stage. Results showed that obtained rule curve with GA, GWO, and IGWO algorithms performed better than FSM. IGWO algorithm outperformed GA and GWO algorithms. We concluded that IGWO algorithm was an effective and powerful tool for developing reservoir rule curve. This research is a fundamental study demonstrating the effectiveness of IGWO algorithm as a promising alternative optimization algorithm for complex reservoir operation problems.

Suggested Citation

  • Youngje Choi & Jungwon Ji & Eunkyung Lee & Sunmi Lee & Sooyeon Yi & Jaeeung Yi, 2023. "Developing Optimal Reservoir Rule Curve for Hydropower Reservoir with an add-on Water Supply Function Using Improved Grey Wolf Optimizer," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(5), pages 2063-2082, March.
  • Handle: RePEc:spr:waterr:v:37:y:2023:i:5:d:10.1007_s11269-023-03478-0
    DOI: 10.1007/s11269-023-03478-0
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    References listed on IDEAS

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    1. Hojat Karami & Sayed Farhad Mousavi & Saeed Farzin & Mohammad Ehteram & Vijay P. Singh & Ozgur Kisi, 2018. "Improved Krill Algorithm for Reservoir Operation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(10), pages 3353-3372, August.
    2. Shi-Mei Choong & A. El-Shafie & W. H. M. Wan Mohtar, 2017. "Optimisation of Multiple Hydropower Reservoir Operation Using Artificial Bee Colony Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(4), pages 1397-1411, March.
    3. Shih, Jhih-Shyang & ReVelle, Charles, 1995. "Water supply operations during drought: A discrete hedging rule," European Journal of Operational Research, Elsevier, vol. 82(1), pages 163-175, April.
    4. Wen-jing Niu & Zhong-kai Feng & Shuai Liu & Yu-bin Chen & Yin-shan Xu & Jun Zhang, 2021. "Multiple Hydropower Reservoirs Operation by Hyperbolic Grey Wolf Optimizer Based on Elitism Selection and Adaptive Mutation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(2), pages 573-591, January.
    5. Youngje Choi & Jaehwang Ahn & Jungwon Ji & Eunkyung Lee & Jaeeung Yi, 2020. "Effects of Inter-Basin Water Transfer Project Operation for Emergency Water Supply," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(8), pages 2535-2548, June.
    6. Gokmen Tayfur, 2017. "Modern Optimization Methods in Water Resources Planning, Engineering and Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(10), pages 3205-3233, August.
    7. Sooyeon Yi & G. Mathias Kondolf & Samuel Sandoval-Solis & Larry Dale, 2022. "Application of Machine Learning-based Energy Use Forecasting for Inter-basin Water Transfer Project," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(14), pages 5675-5694, November.
    8. Ali Jalilian & Majeid Heydari & Arash Azari & Saeid Shabanlou, 2022. "Extracting Optimal Rule Curve of Dam Reservoir Base on Stochastic Inflow," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(6), pages 1763-1782, April.
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