IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v20y2006i2p227-255.html
   My bibliography  Save this article

Water Supply Reservoir Operation by Combined Genetic Algorithm – Linear Programming (GA-LP) Approach

Author

Listed:
  • L. Reis
  • F. Bessler
  • G. Walters
  • D. Savic

Abstract

Multi-reservoir operation planning is a complex task involving many variables, objectives, and decisions. This paper applies a hybrid method using genetic algorithm (GA) and linear programming (LP) developed by the authors to determine operational decisions for a reservoir system over the optimization period. This method identifies part of the decision variables called cost reduction factors (CRFs) by GA and operational variables by LP. CRFs are introduced into the formulation to discourage reservoir depletion in the initial stages of the planning period. These factors are useful parameters that can be employed to determine operational decisions such as optimal releases and imports, in response to future inflow predictions. A part of the Roadford Water Supply System, UK, is used to demonstrate the performance of the GA-LP method in comparison to the RELAX algorithm. The proposed approach obtains comparable results ensuring non zero final storages in the larger reservoirs of the Roadford Hydrosystem. It shows potential for generating operating policy in the form of hegging rules without a priori imposition of their form. Copyright Springer Science + Business Media, Inc. 2006

Suggested Citation

  • L. Reis & F. Bessler & G. Walters & D. Savic, 2006. "Water Supply Reservoir Operation by Combined Genetic Algorithm – Linear Programming (GA-LP) Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 20(2), pages 227-255, April.
    • Handle: RePEc:spr:waterr:v:20:y:2006:i:2:p:227-255
    DOI: 10.1007/s11269-006-8049-z
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11269-006-8049-z
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11269-006-8049-z?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. Ramesh Teegavarapu & Slobodan Simonovic, 2002. "Optimal Operation of Reservoir Systems using Simulated Annealing," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 16(5), pages 401-428, October.
    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. Ruben Menke & Edo Abraham & Panos Parpas & Ivan Stoianov, 2016. "Exploring Optimal Pump Scheduling in Water Distribution Networks with Branch and Bound Methods," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(14), pages 5333-5349, November.
    2. Majid Montaseri & Mahdi Hesami Afshar & Omid Bozorg-Haddad, 2015. "Development of Simulation-Optimization Model (MUSIC-GA) for Urban Stormwater Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(13), pages 4649-4665, October.
    3. João Vieira & Maria Conceição Cunha, 2017. "Nested Optimization Approach for the Capacity Expansion of Multiquality Water Supply Systems under Uncertainty," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(4), pages 1381-1395, March.
    4. Deepti Rani & Maria Moreira, 2010. "Simulation–Optimization Modeling: A Survey and Potential Application 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. 24(6), pages 1107-1138, April.
    5. Chang, Jianxia & Wang, Xiaoyu & Li, Yunyun & Wang, Yimin & Zhang, Hongxue, 2018. "Hydropower plant operation rules optimization response to climate change," Energy, Elsevier, vol. 160(C), pages 886-897.
    6. Abbas Afshar & Fariborz Masoumi & Sam Solis, 2015. "Reliability Based Optimum Reservoir Design by Hybrid ACO-LP Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(6), pages 2045-2058, April.
    7. Md. Hossain & A. El-shafie, 2013. "Intelligent Systems in Optimizing Reservoir Operation Policy: A Review," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(9), pages 3387-3407, July.
    8. Alcigeimes Celeste & Max Billib, 2010. "The Role of Spill and Evaporation in Reservoir Optimization Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(4), pages 617-628, March.
    9. Chunlong Li & Jianzhong Zhou & Shuo Ouyang & Chao Wang & Yi Liu, 2015. "Water Resources Optimal Allocation Based on Large-scale Reservoirs in the Upper Reaches of Yangtze River," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(7), pages 2171-2187, May.

    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. Chuanxiong Kang & Cheng Chen & Jinwen Wang, 2018. "An Efficient Linearization Method for Long-Term Operation of Cascaded Hydropower Reservoirs," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(10), pages 3391-3404, August.
    2. K. Ramakrishnan & C. Suribabu & T. Neelakantan, 2010. "Crop Calendar Adjustment Study for Sathanur Irrigation System in India Using Genetic Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(14), pages 3835-3851, November.
    3. Ludovic Gaudard & Jeannette Gabbi & Andreas Bauder & Franco Romerio, 2016. "Long-term Uncertainty of Hydropower Revenue Due to Climate Change and Electricity Prices," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(4), pages 1325-1343, March.
    4. Nazak Rouzegari & Yousef Hassanzadeh & Mohammad Taghi Sattari, 2019. "Using the Hybrid Simulated Annealing-M5 Tree Algorithms to Extract the If-Then Operation Rules in a Single Reservoir," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(10), pages 3655-3672, August.
    5. Shuo Huang & Xinyu Wu & Yiyang Wu & Zheng Zhang, 2023. "Mid-Term Optimal Scheduling of Low-Head Cascaded Hydropower Stations Considering Inflow Unevenness," Energies, MDPI, vol. 16(17), pages 1-13, September.
    6. Li Chuangang & Ji Changming & Wang Boquan & Liu Minghao & Li Rongbo, 2017. "The Hydropower Station Output Function and its Application in Reservoir Operation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(1), pages 159-172, January.
    7. Mahdi Sedighkia & Asghar Abdoli, 2023. "Design of optimal environmental flow regime at downstream of multireservoir systems by a coupled SWAT-reservoir operation optimization method," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(1), pages 834-854, January.
    8. Dimitrios Karpouzos & Konstantinos Katsifarakis, 2013. "A Set of New Benchmark Optimization Problems for Water Resources Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(9), pages 3333-3348, July.
    9. Mohammad Azizipour & Vahid Ghalenoei & M. H. Afshar & S. S. Solis, 2016. "Optimal Operation of Hydropower Reservoir Systems Using Weed Optimization Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(11), pages 3995-4009, September.
    10. Xun-Gui Li & Xia Wei, 2008. "An Improved Genetic Algorithm-Simulated Annealing Hybrid Algorithm for the Optimization of Multiple Reservoirs," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 22(8), pages 1031-1049, August.
    11. Shinuk Kang & Sangho Lee & Taeuk Kang, 2017. "Development and Application of Storage-Zone Decision Method for Long-Term Reservoir Operation Using the Dynamically Dimensioned Search Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(1), pages 219-232, January.
    12. Bin Xu & Ping-An Zhong & Xinyu Wan & Weiguo Zhang & Xuan Chen, 2012. "Dynamic Feasible Region Genetic Algorithm for Optimal Operation of a Multi-Reservoir System," Energies, MDPI, vol. 5(8), pages 1-17, August.
    13. Deepti Rani & Maria Moreira, 2010. "Simulation–Optimization Modeling: A Survey and Potential Application 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. 24(6), pages 1107-1138, April.
    14. Fang-Fang Li & Jun Qiu, 2015. "Multi-Objective Reservoir Optimization Balancing Energy Generation and Firm Power," Energies, MDPI, vol. 8(7), pages 1-15, July.
    15. Tibebe Dessalegne & John Nicklow, 2012. "Artificial Life Algorithm for Management of Multi-reservoir River Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(5), pages 1125-1141, March.
    16. Ruben Menke & Edo Abraham & Panos Parpas & Ivan Stoianov, 2016. "Exploring Optimal Pump Scheduling in Water Distribution Networks with Branch and Bound Methods," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(14), pages 5333-5349, November.
    17. Abolfazl Baniasadi Moghadam & Hossein Ebrahimi & Abbas Khashei Siuki & Abolfazl Akbarpour, 2022. "Reliability-based Operation of Reservoirs Using Combined Monte Carlo Simulation Model and a Novel Nature-inspired Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(12), pages 4447-4468, September.
    18. Ludovic Gaudard & Jeannette Gabbi & Andreas Bauder & Franco Romerio, 2016. "Long-term Uncertainty of Hydropower Revenue Due to Climate Change and Electricity Prices," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(4), pages 1325-1343, March.
    19. Fang, Zhou & Liao, Shengli & Cheng, Chuntian & Zhao, Hongye & Liu, Benxi & Su, Huaying, 2023. "Parallel improved DPSA algorithm for medium-term optimal scheduling of large-scale cascade hydropower plants," Renewable Energy, Elsevier, vol. 210(C), pages 134-147.
    20. Coelho, B. & Andrade-Campos, A., 2014. "Efficiency achievement in water supply systems—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 59-84.

    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:20:y:2006:i:2:p:227-255. 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.