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Optimization of Water Resources Utilization by PSO-GA

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  • Jian-xia Chang
  • Tao Bai
  • Qiang Huang
  • Da-wen Yang

Abstract

The objective of this paper is to present an optimal model to address the water resources utilization of the Tao River basin in China. The Tao River water diversion project has been proposed to alleviate the problem of water shortages in Gansu Province in China. A multi reservoir system is under consideration with multiple objectives including water diversion, ecological water demand, irrigation, hydropower generation, industrial requirements, and domestic uses in the Tao River basin. A multi-objective model for the minimization of water shortages and the maximization of hydro-power production is proposed to manage the utilization of Tao River water resources. An adjustable PSO-GA (particle swarm optimization – genetic algorithm) hybrid algorithm is proposed that combines the strengths of PSO and GA to balance natural selection and good knowledge sharing to enable a robust and efficient search of the solution space. Two driving parameters are used in the adjustable hybrid model to optimize the performance of the PSO-GA hybrid algorithm by assigning a preference to either PSO or GA. The results show that the proposed hybrid algorithm can simultaneously obtain a promising solution and speed up the convergence. Copyright Springer Science+Business Media Dordrecht 2013

Suggested Citation

  • 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.
  • Handle: RePEc:spr:waterr:v:27:y:2013:i:10:p:3525-3540
    DOI: 10.1007/s11269-013-0362-8
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    References listed on IDEAS

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    Cited by:

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    2. 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.
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    5. Fang Wan & Wenlin Yuan & Jin Zhou, 2017. "Derivation of Tri-level Programming Model for Multi-Reservoir Optimal Operation in Inter-Basin Transfer-Diversion-Supply Project," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(1), pages 479-494, January.
    6. 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.
    7. Wang Zhang & Pan Liu & Xizhen Chen & Li Wang & Xueshan Ai & Maoyuan Feng & Dedi Liu & Yuanyuan Liu, 2016. "Optimal Operation of Multi-reservoir Systems Considering Time-lags of Flood Routing," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(2), pages 523-540, January.
    8. Ak, Mumtaz & Kentel, Elcin & Savasaneril, Secil, 2017. "Operating policies for energy generation and revenue management in single-reservoir hydropower systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 1253-1261.
    9. Reza Hajiabadi & Mahdi Zarghami, 2014. "Multi-Objective Reservoir Operation with Sediment Flushing; Case Study of Sefidrud Reservoir," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(15), pages 5357-5376, December.
    10. Wang Zhang & Pan Liu & Xizhen Chen & Li Wang & Xueshan Ai & Maoyuan Feng & Dedi Liu & Yuanyuan Liu, 2016. "Optimal Operation of Multi-reservoir Systems Considering Time-lags of Flood Routing," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(2), pages 523-540, January.
    11. Mohit Agarwal & Gur Mauj Saran Srivastava, 2018. "Genetic Algorithm-Enabled Particle Swarm Optimization (PSOGA)-Based Task Scheduling in Cloud Computing Environment," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 17(04), pages 1237-1267, July.
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    14. Bo Ming & Jian-xia Chang & Qiang Huang & Yi-min Wang & Sheng-zhi Huang, 2015. "Optimal Operation of Multi-Reservoir System Based-On Cuckoo Search Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(15), pages 5671-5687, December.
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