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Application of Fixed Length Gene Genetic Programming (FLGGP) in Hydropower Reservoir Operation

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  • Habib Akbari-Alashti
  • Omid Bozorg Haddad
  • Miguel Mariño

Abstract

This paper develops a new method for real-time operation of reservoir systems. Genetic programming (GP) and a developed fixed length gene GP (FLGGP) are applied and compared in two approaches of static and dynamic operation rules with the aim of hydroelectric supply of Karun3 reservoir in Iran. Results are compared with those of genetic algorithm (GA) and nonlinear programming (NLP) method, indicating that GP and FLGGP have a higher efficiency (on average, 5 %) than GA and NLP operation methods. In addition, results showed that the FLGGP method is a powerful and efficient tool without the limitations of GP and can be used as a suitable replacement to GP. Comparison of two approaches of static and dynamic operation rules demonstrated the superiority of dynamic operation rules and this approach has an average superiority of 10 % to static operation rules in all methods. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • Habib Akbari-Alashti & Omid Bozorg Haddad & Miguel Mariño, 2015. "Application of Fixed Length Gene Genetic Programming (FLGGP) in Hydropower Reservoir Operation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(9), pages 3357-3370, July.
    • Handle: RePEc:spr:waterr:v:29:y:2015:i:9:p:3357-3370
    DOI: 10.1007/s11269-015-1003-1
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    References listed on IDEAS

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    1. Richard E. Rosenthal, 1981. "A Nonlinear Network Flow Algorithm for Maximization of Benefits in a Hydroelectric Power System," Operations Research, INFORMS, vol. 29(4), pages 763-786, August.
    2. C. Sivapragasam & G. Vasudevan & P. Vincent, 2007. "Effect of inflow forecast accuracy and operating time horizon in optimizing irrigation releases," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(6), pages 933-945, June.
    3. Ashkan Shokri & Omid Bozorg Haddad & Miguel Mariño, 2013. "Algorithm for Increasing the Speed of Evolutionary Optimization and its Accuracy in Multi-objective Problems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(7), pages 2231-2249, May.
    4. S. Seifollahi-Aghmiuni & Omid Bozorg Haddad & M. Omid & M. Mariño, 2013. "Effects of Pipe Roughness Uncertainty on Water Distribution Network Performance During its Operational Period," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(5), pages 1581-1599, March.
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    Cited by:

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    2. V. Ramaswamy & F. Saleh, 2020. "Ensemble Based Forecasting and Optimization Framework to Optimize Releases from Water Supply Reservoirs for Flood Control," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(3), pages 989-1004, February.
    3. 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.
    4. 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.
    5. 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.
    6. 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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