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Operation Policies through Dynamic Programming and Genetic Algorithms, for a Reservoir with Irrigation and Water Supply Uses

Author

Listed:
  • Rosalva Mendoza Ramírez

    (Universidad Nacional Autónoma de México, Instituto de Ingeniería, Campus Morelia)

  • Maritza Liliana Arganis Juárez

    (Universidad Nacional Autónoma de México, Instituto de Ingeniería)

  • Ramón Domínguez Mora

    (Universidad Nacional Autónoma de México, Instituto de Ingeniería)

  • Luis Daniel Padilla Morales

    (Universidad Nacional Autónoma de México, Instituto de Ingeniería)

  • Óscar Arturo Fuentes Mariles

    (Universidad Nacional Autónoma de México, Instituto de Ingeniería)

  • Alejandro Mendoza Reséndiz

    (Universidad Nacional Autónoma de México, Instituto de Ingeniería)

  • Eliseo Carrizosa Elizondo

    (Universidad Nacional Autónoma de México, Instituto de Ingeniería)

  • Rafael Bernardo Carmona Paredes

    (Universidad Nacional Autónoma de México, Instituto de Ingeniería)

Abstract

In this study, operation policies were obtained for a reservoir in Michoacán, Mexico, used for irrigation and domestic water supplies. The main purpose of these policies is to optimize the uses of the water, an increasingly scarce resource everywhere. Two optimization methodologies were used; stochastic dynamic programming, that provides release decisions for each stage, and genetic algorithms coupled with a reservoir operation simulation program, to achieve annual release curves. The operation of the reservoir was evaluated using historical inflow records. Monthly requirements for crop cycles, as well as the volumes of spills and deficits were examined. Both methodologies gave inverse relationships between deficits and spilled volumes. While both methodologies proved efficient in achieving the objectives, the results of the stochastic dynamic programming showed a better performance for this system.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:waterr:v:35:y:2021:i:5:d:10.1007_s11269-021-02802-w
    DOI: 10.1007/s11269-021-02802-w
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    References listed on IDEAS

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    1. Qiao-feng Tan & Guo-hua Fang & Xin Wen & Xiao-hui Lei & Xu Wang & Chao Wang & Yi Ji, 2020. "Bayesian Stochastic Dynamic Programming for Hydropower Generation Operation Based on Copula Functions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(5), pages 1589-1607, March.
    2. Hojat Karami & Saeed Farzin & Aylin Jahangiri & Mohammad Ehteram & Ozgur Kisi & Ahmed El-Shafie, 2019. "Multi-Reservoir System Optimization Based on Hybrid Gravitational Algorithm to Minimize Water-Supply Deficiencies," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(8), pages 2741-2760, June.
    3. 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.
    4. Katakam V SeethaRam, 2021. "Three Level Rule Curve for Optimum Operation of a Multipurpose Reservoir using Genetic Algorithms," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(1), pages 353-368, January.
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    Cited by:

    1. Chen Wang & Yizi Shang & Majid Khayatnezhad, 2021. "Fuzzy Stress-based Modeling for Probabilistic Irrigation Planning Using Copula-NSPSO," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(14), pages 4943-4959, November.
    2. Arya Yaghoubzadeh-Bavandpour & Omid Bozorg-Haddad & Mohammadreza Rajabi & Babak Zolghadr-Asli & Xuefeng Chu, 2022. "Application of Swarm Intelligence and Evolutionary Computation Algorithms for Optimal Reservoir Operation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(7), pages 2275-2292, May.

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