IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v37y2023i5d10.1007_s11269-023-03478-0.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11269-023-03478-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11269-023-03478-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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. 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.
    3. 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.
    4. 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.
    5. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Burhan Yildiz & Mehtap Kose Ulukok & Vali Bashiry, 2023. "Bi-Attempted Base Optimization Algorithm on Optimization of Hydrosystems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(9), pages 3585-3597, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zaher Mundher Yaseen & Mohammad Ehteram & Md. Shabbir Hossain & Chow Ming Fai & Suhana Binti Koting & Nuruol Syuhadaa Mohd & Wan Zurina Binti Jaafar & Haitham Abdulmohsin Afan & Lai Sai Hin & Nuratiah, 2019. "A Novel Hybrid Evolutionary Data-Intelligence Algorithm for Irrigation and Power Production Management: Application to Multi-Purpose Reservoir Systems," Sustainability, MDPI, vol. 11(7), pages 1-28, April.
    2. Amir Hatamkhani & Mojtaba Shourian & Ali Moridi, 2021. "Optimal Design and Operation of a Hydropower Reservoir Plant Using a WEAP-Based Simulation–Optimization Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(5), pages 1637-1652, March.
    3. George Tsakiris, 2017. "Facets of Modern Water Resources Management: Prolegomena," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(10), pages 2899-2904, August.
    4. Sarmad Dashti Latif & Ali Najah Ahmed, 2023. "A review of deep learning and machine learning techniques for hydrological inflow forecasting," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(11), pages 12189-12216, November.
    5. Yong Peng & Jinggang Chu & Anbang Peng & Huicheng Zhou, 2015. "Optimization Operation Model Coupled with Improving Water-Transfer Rules and Hedging Rules for Inter-Basin Water Transfer-Supply Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(10), pages 3787-3806, August.
    6. Beshavard, Mahdi & Adib, Arash & Ashrafi, Seyed Mohammad & Kisi, Ozgur, 2022. "Establishing effective warning storage to derive optimal reservoir operation policy based on the drought condition," Agricultural Water Management, Elsevier, vol. 274(C).
    7. Iman Ahmadianfar & Bijay Halder & Salim Heddam & Leonardo Goliatt & Mou Leong Tan & Zulfaqar Sa’adi & Zainab Al-Khafaji & Raad Z. Homod & Tarik A. Rashid & Zaher Mundher Yaseen, 2023. "An Enhanced Multioperator Runge–Kutta Algorithm for Optimizing Complex Water Engineering Problems," Sustainability, MDPI, vol. 15(3), pages 1-28, January.
    8. Babak Mohammadi & Farshad Ahmadi & Saeid Mehdizadeh & Yiqing Guan & Quoc Bao Pham & Nguyen Thi Thuy Linh & Doan Quang Tri, 2020. "Developing Novel Robust Models to Improve the Accuracy of Daily Streamflow Modeling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(10), pages 3387-3409, August.
    9. Alireza Dariane & Farzane Karami, 2014. "Deriving Hedging Rules of Multi-Reservoir System by Online Evolving Neural Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(11), pages 3651-3665, September.
    10. Hui Wang & Junguo Liu, 2013. "Reservoir Operation Incorporating Hedging Rules and Operational Inflow Forecasts," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(5), pages 1427-1438, March.
    11. Ahmadi, Esmaeil & McLellan, Benjamin & Tezuka, Tetsuo, 2020. "The economic synergies of modelling the renewable energy-water nexus towards sustainability," Renewable Energy, Elsevier, vol. 162(C), pages 1347-1366.
    12. Wen-jing Niu & Zhong-kai Feng & Yu-rong Li & Shuai Liu, 2021. "Cooperation Search Algorithm for Power Generation Production Operation Optimization of Cascade Hydropower Reservoirs," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(8), pages 2465-2485, June.
    13. Mahboubeh Khorsandi & Parisa-Sadat Ashofteh & Firoozeh Azadi & Xuefeng Chu, 2022. "Multi-Objective Firefly Integration with the K-Nearest Neighbor to Reduce Simulation Model Calls to Accelerate the Optimal Operation of Multi-Objective Reservoirs," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(9), pages 3283-3304, July.
    14. Gi Joo Kim & Young-Oh Kim, 2021. "How Does the Coupling of Real-World Policies with Optimization Models Expand the Practicality of Solutions in Reservoir Operation Problems?," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(10), pages 3121-3137, August.
    15. T. Neelakantan & N. Pundarikanthan, 1999. "Hedging Rule Optimisation for Water Supply Reservoirs System," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 13(6), pages 409-426, December.
    16. Vakilifard, Negar & A. Bahri, Parisa & Anda, Martin & Ho, Goen, 2019. "An interactive planning model for sustainable urban water and energy supply," Applied Energy, Elsevier, vol. 235(C), pages 332-345.
    17. Jenq-Tzong Shiau & Hsu-Hui Wen & I-Wen Su, 2021. "Comparing Optimal Hedging Policies Incorporating Past Operation Information and Future Hydrologic Information," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(7), pages 2177-2196, May.
    18. Danyang Di & Qi Shi & Zening Wu & Huiliang Wang, 2023. "Sustainable Management and Environmental Protection for Basin Water Allocation: Differential Game-based Multiobjective Programming," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(1), pages 1-20, January.
    19. Inkyung Min & Nakyung Lee & Sanha Kim & Yelim Bang & Juyeon Jang & Kichul Jung & Daeryong Park, 2024. "An Improved Aggregation–Decomposition Optimization Approach for Ecological Flow Supply in Parallel Reservoir Systems," Sustainability, MDPI, vol. 16(17), pages 1-22, August.
    20. Bao-Jian Li & Guo-Liang Sun & Yan Liu & Wen-Chuan Wang & Xu-Dong Huang, 2022. "Monthly Runoff Forecasting Using Variational Mode Decomposition Coupled with Gray Wolf Optimizer-Based Long Short-term Memory Neural Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(6), pages 2095-2115, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:waterr:v:37:y:2023:i:5:d:10.1007_s11269-023-03478-0. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.