IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v36y2022i6d10.1007_s11269-022-03087-3.html
   My bibliography  Save this article

Extracting Optimal Rule Curve of Dam Reservoir Base on Stochastic Inflow

Author

Listed:
  • Ali Jalilian

    (Bu-Ali Sina University)

  • Majeid Heydari

    (Bu-Ali Sina University)

  • Arash Azari

    (Razi University)

  • Saeid Shabanlou

    (Islamic Azad University)

Abstract

Declining rainfall, development of agricultural and industrial activities, population growth as well as Iran's location in arid and semi-arid regions of the planet have led to a shortage of water resources and a lack of supply, especially in low-water years. One of the appropriate solutions in this regard is the optimal operation of available resources as well as its storage and maintenance for critical conditions. In most deterministic optimization techniques, the optimal parameters of reservoir operation are extracted based on a certain series of inflow which cannot be generalized to other series of inflow to the reservoir. In this paper, an operation model based on the Parameterization Simulation- Optimization (PSO) method is utilized in which considering stochastic conditions of inflow, the optimal parameters of rationing are determined via the link of the reservoir simulation model to the NSGA-II multi-objective optimization algorithm. In the mentioned model, the combination of the stochastic data and part of historical data (a total of 4,800 months) are used to optimize the system and extract optimal operation rules. Moreover, to verify the developed model, the combination of the stochastic data and the remaining of historical values (a total of 372 months) are utilized. Finally, the results obtained from the model are compared with those of the standard operating policy (SOP). The result reveals that compared to the SOP, the PSO model based on parameterization of the reservoir works better in managing the allocation of demands in the dry and wet months and preventing the reservoir from emptying.

Suggested Citation

  • 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.
  • Handle: RePEc:spr:waterr:v:36:y:2022:i:6:d:10.1007_s11269-022-03087-3
    DOI: 10.1007/s11269-022-03087-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11269-022-03087-3
    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/s11269-022-03087-3?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. Arash Azari & Saeid Hamzeh & Saba Naderi, 2018. "Multi-Objective Optimization of the Reservoir System Operation by Using the Hedging Policy," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(6), pages 2061-2078, 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. 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.
    2. 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.

    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. Seyedeh Hadis Moghadam & Parisa-Sadat Ashofteh & Hugo A. Loáiciga, 2022. "Optimal Water Allocation of Surface and Ground Water Resources Under Climate Change with WEAP and IWOA Modeling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(9), pages 3181-3205, July.
    2. Behrang Beiranvand & Parisa-Sadat Ashofteh, 2023. "A Systematic Review of Optimization of Dams Reservoir Operation Using the Meta-heuristic Algorithms," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(9), pages 3457-3526, July.
    3. Rosalva Mendoza Ramírez & Maritza Liliana Arganis Juárez & Ramón Domínguez Mora & Luis Daniel Padilla Morales & Óscar Arturo Fuentes Mariles & Alejandro Mendoza Reséndiz & Eliseo Carrizosa Elizondo & , 2021. "Operation Policies through Dynamic Programming and Genetic Algorithms, for a Reservoir with Irrigation and Water Supply Uses," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(5), pages 1573-1586, March.
    4. Dariane, A.B. & Ghasemi, M. & Karami, F. & Azaranfar, A. & Hatami, S., 2021. "Crop pattern optimization in a multi-reservoir system by combining many-objective and social choice methods," Agricultural Water Management, Elsevier, vol. 257(C).
    5. Rui Yang & Yutao Qi & Jiaojiao Lei & Xiaoliang Ma & Haibin Zhang, 2022. "A Parallel Multi-objective Optimization Algorithm Based on Coarse-to-Fine Decomposition for Real-time Large-scale Reservoir Flood Control Operation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(9), pages 3207-3219, July.
    6. Wenyuan Jiang & Zhenxiang Zeng & Zhengyun Zhang & Yichen Zhao, 2022. "Regulation and Optimization of Urban Water and Land Resources Utilization for Low Carbon Development: A Case Study of Tianjin, China," Sustainability, MDPI, vol. 14(5), pages 1-22, February.

    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:36:y:2022:i:6:d:10.1007_s11269-022-03087-3. 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.