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Genetic Algorithms for Optimal Reservoir Dispatching

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  • Chang Jian-Xia
  • Huang Qiang
  • Wang Yi-min

Abstract

The fundamental guidelines for genetic algorithm to optimal reservoir dispatching have been introduced. It is concluded that with three basic generators selection, crossover and mutation genetic algorithm could search the optimum solution or near-optimal solution to a complex water resources problem. Alternative formulation schemes of a GA are considered. The real-value coding is proved significantly faster than binary coding, and can produce better results. Sensitivity of crossover probability and mutation probability are also analyzed in this paper. Results from genetic algorithm with real-value coding are compared with those from other optimal methods. The results demonstrate that a genetic algorithm can be satisfactorily used in optimal reservoir problems, and it has potential in application to complex river systems. Copyright Springer Science + Business Media, Inc. 2005

Suggested Citation

  • Chang Jian-Xia & Huang Qiang & Wang Yi-min, 2005. "Genetic Algorithms for Optimal Reservoir Dispatching," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 19(4), pages 321-331, August.
    • Handle: RePEc:spr:waterr:v:19:y:2005:i:4:p:321-331
    DOI: 10.1007/s11269-005-3018-5
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    Citations

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    Cited by:

    1. J. Yazdi & A. Moridi, 2018. "Multi-Objective Differential Evolution for Design of Cascade Hydropower Reservoir Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(14), pages 4779-4791, November.
    2. Gilboa, Yael & Friedler, Eran & Gal, Gideon, 2009. "Adapting empirical equations to Lake Kinneret data by using three calibration methods," Ecological Modelling, Elsevier, vol. 220(23), pages 3291-3300.
    3. T. Fowe & I. Nouiri & B. Ibrahim & H. Karambiri & J. Paturel, 2015. "OPTIWAM: An Intelligent Tool for Optimizing Irrigation Water Management in Coupled Reservoir–Groundwater 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 3841-3861, August.
    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. Jian-xia Chang & Tao Bai & Qiang Huang & Da-wen Yang, 2013. "Optimization of Water Resources Utilization by PSO-GA," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(10), pages 3525-3540, August.
    6. 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.
    7. Jatin Anand & Ashvani Kumar Gosain & Rakesh Khosa, 2018. "Optimisation of Multipurpose Reservoir Operation by Coupling Soil and Water Assessment Tool (SWAT) and Genetic Algorithm for Optimal Operating Policy (Case Study: Ganga River Basin)," Sustainability, MDPI, vol. 10(5), pages 1-20, May.
    8. V. Jothiprakash & R. Arunkumar, 2013. "Optimization of Hydropower Reservoir Using Evolutionary Algorithms Coupled with Chaos," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(7), pages 1963-1979, May.
    9. Seyed-Mohammad Hosseini-Moghari & Reza Morovati & Mohammad Moghadas & Shahab Araghinejad, 2015. "Optimum Operation of Reservoir Using Two Evolutionary Algorithms: Imperialist Competitive Algorithm (ICA) and Cuckoo Optimization Algorithm (COA)," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(10), pages 3749-3769, August.
    10. Xinyu Wu & Rui Guo & Xilong Cheng & Chuntian Cheng, 2021. "Combined Aggregated Sampling Stochastic Dynamic Programming and Simulation-Optimization to Derive Operation Rules for Large-Scale Hydropower System," Energies, MDPI, vol. 14(3), pages 1-15, January.

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