IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v33y2019i8d10.1007_s11269-019-02238-3.html
   My bibliography  Save this article

Multi-Reservoir System Optimization Based on Hybrid Gravitational Algorithm to Minimize Water-Supply Deficiencies

Author

Listed:
  • Hojat Karami

    (Semnan University)

  • Saeed Farzin

    (Semnan University)

  • Aylin Jahangiri

    (Semnan University)

  • Mohammad Ehteram

    (Semnan University)

  • Ozgur Kisi

    (Ilia State University)

  • Ahmed El-Shafie

    (University of Malaya)

Abstract

The growing prevalence of droughts and water scarcity have increased the importance of operating dam and reservoir systems efficiently. Several methods based on algorithms have been developed in recent years in a bid to optimize water release operation policy, in order to overcome or minimize the impact of droughts. However, all of these algorithms suffer from some weaknesses or drawbacks – notably early convergence, a low rate of convergence, or trapping in local optimizations – that limit their effectiveness and efficiency in seeking to determine the global optima for the operation of water systems. Against this background, the present study seeks to introduce and test a Hybrid Algorithm (HA) which integrates the Gravitational Search Algorithm (GSA) with the Particle Swarm Optimization Algorithm (PSOA) with the goal of minimizing irrigation deficiencies in a multi-reservoir system. The proposed algorithm was tested for a specific important multi-reservoir system in Iran: namely the Golestan Dam and Voshmgir Dam system. The results showed that applying the HA could reduce average irrigation deficiencies for the Golestan Dam substantially, to only 2 million cubic meters (MCM), compared to deficiency values for the Genetic Algorithm (GA), PSOA and GSA of 15.1, 6.7 and 5.8 MCM respectively. In addition, the HA performed very efficiently, reducing substantially the computational time needed to achieve the global optimal when compared with the other algorithms tested. Furthermore, the HA showed itself capable of assuring a high volumetric reliability index (VRI) to meet the pattern of water demand downstream from the dams, as well as clearly outperforming the other algorithms on other important indices. In conclusion, the proposed HA seems to offer considerable potential as an optimizer for dam and reservoir operations world-wide.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:waterr:v:33:y:2019:i:8:d:10.1007_s11269-019-02238-3
    DOI: 10.1007/s11269-019-02238-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11269-019-02238-3
    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/s11269-019-02238-3?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. Y. Bolouri-Yazdeli & O. Bozorg Haddad & E. Fallah-Mehdipour & M. Mariño, 2014. "Evaluation of Real-Time Operation Rules in Reservoir Systems Operation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(3), pages 715-729, February.
    2. Yong Peng & Anbang Peng & Xiaoli Zhang & Huicheng Zhou & Lin Zhang & Wenzhong Wang & Zixin Zhang, 2017. "Multi-Core Parallel Particle Swarm Optimization for the Operation of 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. 31(1), pages 27-41, January.
    3. Feng, Zhong-kai & Niu, Wen-jing & Cheng, Chun-tian, 2017. "Multi-objective quantum-behaved particle swarm optimization for economic environmental hydrothermal energy system scheduling," Energy, Elsevier, vol. 131(C), pages 165-178.
    4. K. Srinivasan & Kranthi Kumar, 2018. "Multi-Objective Simulation-Optimization Model for Long-term Reservoir Operation using Piecewise Linear Hedging Rule," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(5), pages 1901-1911, March.
    5. Hamid Bashiri-Atrabi & Kourosh Qaderi & David Rheinheimer & Erfaneh Sharifi, 2015. "Application of Harmony Search Algorithm to Reservoir Operation Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(15), pages 5729-5748, December.
    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. Salah L. Zubaidi & Sandra Ortega-Martorell & Patryk Kot & Rafid M. Alkhaddar & Mawada Abdellatif & Sadik K. Gharghan & Maytham S. Ahmed & Khalid Hashim, 2020. "A Method for Predicting Long-Term Municipal Water Demands Under Climate Change," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(3), pages 1265-1279, February.
    2. Sarmad Dashti Latif & Suzlyana Marhain & Md Shabbir Hossain & Ali Najah Ahmed & Mohsen Sherif & Ahmed Sefelnasr & Ahmed El-Shafie, 2021. "Optimizing the Operation Release Policy Using Charged System Search Algorithm: A Case Study of Klang Gates Dam, Malaysia," Sustainability, MDPI, vol. 13(11), pages 1-19, May.
    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. Mohammad Ehteram & Ali Najah Ahmed & Ming Fai Chow & Sarmad Dashti Latif & Kwok-wing Chau & Kai Lun Chong & Ahmed El-Shafie, 2023. "Optimal operation of hydropower reservoirs under climate change," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(10), pages 10627-10659, October.
    5. Mehrabi, Ahmad & Heidarpour, Manouchehr & Safavi, Hamid R. & Rezaei, Farshad, 2021. "Assessment of the optimized scenarios for economic-environmental conjunctive water use utilizing gravitational search algorithm," Agricultural Water Management, Elsevier, vol. 246(C).

    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. Thibaut Cuvelier & Pierre Archambeau & Benjamin Dewals & Quentin Louveaux, 2018. "Comparison Between Robust and Stochastic Optimisation for Long-term Reservoir Management Under Uncertainty," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(5), pages 1599-1614, March.
    2. Feng, Zhong-kai & Niu, Wen-jing & Cheng, Chun-tian, 2019. "China’s large-scale hydropower system: operation characteristics, modeling challenge and dimensionality reduction possibilities," Renewable Energy, Elsevier, vol. 136(C), pages 805-818.
    3. Feng, Zhong-kai & Niu, Wen-jing & Cheng, Chun-tian, 2018. "Optimization of hydropower reservoirs operation balancing generation benefit and ecological requirement with parallel multi-objective genetic algorithm," Energy, Elsevier, vol. 153(C), pages 706-718.
    4. 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.
    5. Fatemeh Barzegari Banadkooki & Jan Adamowski & Vijay P. Singh & Mohammad Ehteram & Hojat Karami & Sayed Farhad Mousavi & Saeed Farzin & Ahmed EL-Shafie, 2020. "Crow Algorithm for Irrigation Management: A Case Study," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(3), pages 1021-1045, February.
    6. Feng, Zhong-kai & Niu, Wen-jing & Cheng, Chun-tian & Wu, Xin-yu, 2017. "Optimization of hydropower system operation by uniform dynamic programming for dimensionality reduction," Energy, Elsevier, vol. 134(C), pages 718-730.
    7. Feng, Zhong-kai & Niu, Wen-jing & Wang, Wen-chuan & Zhou, Jian-zhong & Cheng, Chun-tian, 2019. "A mixed integer linear programming model for unit commitment of thermal plants with peak shaving operation aspect in regional power grid lack of flexible hydropower energy," Energy, Elsevier, vol. 175(C), pages 618-629.
    8. Chang, Jianxia & Li, Yunyun & Yuan, Meng & Wang, Yimin, 2017. "Efficiency evaluation of hydropower station operation: A case study of Longyangxia station in the Yellow River, China," Energy, Elsevier, vol. 135(C), pages 23-31.
    9. Mojtaba Moravej & Seyed-Mohammad Hosseini-Moghari, 2016. "Large Scale Reservoirs System Operation Optimization: the Interior Search Algorithm (ISA) Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(10), pages 3389-3407, August.
    10. Mohammad Ehteram & Hojat Karami & Sayed Farhad Mousavi & Saaed Farzin & Alcigeimes B. Celeste & Ahmad-El Shafie, 2018. "Reservoir Operation by a New Evolutionary Algorithm: Kidney Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(14), pages 4681-4706, November.
    11. Chang-ming Ji & Ting Zhou & Hai-tao Huang, 2014. "Operating Rules Derivation of Jinsha Reservoirs System with Parameter Calibrated Support Vector Regression," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(9), pages 2435-2451, July.
    12. Tao Bai & Lianzhou Wu & Jian-xia Chang & Qiang Huang, 2015. "Multi-Objective Optimal Operation Model of Cascade Reservoirs and Its Application on Water and Sediment Regulation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(8), pages 2751-2770, June.
    13. Yi Liu & Zhiqiang Jiang & Zhongkai Feng & Yuyun Chen & Hairong Zhang & Ping Chen, 2019. "Optimization of Energy Storage Operation Chart of Cascade Reservoirs with Multi-Year Regulating Reservoir," Energies, MDPI, vol. 12(20), pages 1-20, October.
    14. Wenlin Yuan & Xueyan Yu & Chengguo Su & Denghua Yan & Zening Wu, 2020. "A Multi-Timescale Integrated Operation Model for Balancing Power Generation, Ecology, and Water Supply of Reservoir Operation," Energies, MDPI, vol. 14(1), pages 1-21, December.
    15. Vartika Paliwal & Aniruddha D. Ghare & Ashwini B. Mirajkar & Neeraj Dhanraj Bokde & Andrés Elías Feijóo Lorenzo, 2019. "Computer Modeling for the Operation Optimization of Mula Reservoir, Upper Godavari Basin, India, Using the Jaya Algorithm," Sustainability, MDPI, vol. 12(1), pages 1-21, December.
    16. Dong Liu & Zhihuai Xiao & Hongtao Li & Dong Liu & Xiao Hu & O.P. Malik, 2019. "Accurate Parameter Estimation of a Hydro-Turbine Regulation System Using Adaptive Fuzzy Particle Swarm Optimization," Energies, MDPI, vol. 12(20), pages 1-21, October.
    17. Liao, Shengli & Liu, Huan & Liu, Benxi & Liu, Tian & Li, Chonghao & Su, Huaying, 2023. "Solution framework for short-term cascade hydropower system optimization operations based on the load decomposition strategy," Energy, Elsevier, vol. 277(C).
    18. 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.
    19. Parisa-Sadat Ashofteh & Omid Bozorg-Haddad & Hugo A. Loáiciga, 2017. "Multi-Criteria Environmental Impact Assessment of Alternative Irrigation Networks with an Adopted Matrix-Based Method," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(3), pages 903-928, February.
    20. Zhong-kai Feng & Wen-jing Niu & Zhi-qiang Jiang & Hui Qin & Zhen-guo Song, 2020. "Monthly Operation Optimization of Cascade Hydropower Reservoirs with Dynamic Programming and Latin Hypercube Sampling for Dimensionality Reduction," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(6), pages 2029-2041, 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:33:y:2019:i:8:d:10.1007_s11269-019-02238-3. 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.