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Operation of storage reservoir for water quality by using optimization and artificial intelligence techniques

Author

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  • Chaves, Paulo
  • Tsukatani, Tsuneo
  • Kojiri, Toshiharu

Abstract

Water quantity and quality are considered to be the main driving forces of the reservoir operation. Barra Bonita reservoir, located in the southeast region of Brazil, is chosen as the case study for the application of the proposed methodology. Herein, optimization and artificial intelligence (AI) techniques are applied in the simulation and operation of the reservoir. A fuzzy stochastic dynamic programming model (FSDP) is developed for calculating the optimal operation procedures. Optimization is applied to achieve multiple fuzzy objectives. Markov chain technique is applied to handle the stochastic characteristics of river flow. Water quality analysis is carried out using an artificial neural network model. Organic matter and nutrient loads are modeled as a function of river discharge through the application of a fuzzy regression model based on fuzzy performance functions. The obtained results show that the proposed methodology provides an effective and useful tool for reservoir operation.

Suggested Citation

  • Chaves, Paulo & Tsukatani, Tsuneo & Kojiri, Toshiharu, 2004. "Operation of storage reservoir for water quality by using optimization and artificial intelligence techniques," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 67(4), pages 419-432.
    • Handle: RePEc:eee:matcom:v:67:y:2004:i:4:p:419-432
    DOI: 10.1016/j.matcom.2004.06.005
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    Citations

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    Cited by:

    1. Gonçalves, F.V. & Costa, L.H. & Ramos, H.M., 2011. "Best economical hybrid energy solution: Model development and case study of a WDS in Portugal," Energy Policy, Elsevier, vol. 39(6), pages 3361-3369, June.
    2. Swades Pal, 2017. "Impact of Tilpara barrage on backwater reach of Kushkarni River: a tributary of Mayurakshi River," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 19(5), pages 2115-2142, October.
    3. Andre Ferreira & Ramesh Teegavarapu, 2012. "Optimal and Adaptive Operation of a Hydropower System with Unit Commitment and Water Quality Constraints," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(3), pages 707-732, February.
    4. Kisi, Özgür, 2008. "Constructing neural network sediment estimation models using a data-driven algorithm," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(1), pages 94-103.
    5. Qing Gu & Ke Wang & Jiadan Li & Ligang Ma & Jinsong Deng & Kefeng Zheng & Xiaobin Zhang & Li Sheng, 2015. "Spatio-Temporal Trends and Identification of Correlated Variables with Water Quality for Drinking-Water Reservoirs," IJERPH, MDPI, vol. 12(10), pages 1-16, October.
    6. F. Gonçalves & L. Costa & Helena Ramos, 2011. "ANN for Hybrid Energy System Evaluation: Methodology and WSS Case Study," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(9), pages 2295-2317, July.
    7. Alireza Dariane & Farzane Karami, 2014. "Deriving Hedging Rules of Multi-Reservoir System by Online Evolving Neural Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(11), pages 3651-3665, September.
    8. Ashkan Shokri & Omid Bozorg Haddad & Miguel Mariño, 2014. "Multi-Objective Quantity–Quality Reservoir Operation in Sudden Pollution," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(2), pages 567-586, January.
    9. Tsai, Wen-Ping & Cheng, Chung-Lien & Uen, Tinn-Shuan & Zhou, Yanlai & Chang, Fi-John, 2019. "Drought mitigation under urbanization through an intelligent water allocation system," Agricultural Water Management, Elsevier, vol. 213(C), pages 87-96.
    10. Xu, Jiuping & Tao, Zhimiao, 2012. "A class of multi-objective equilibrium chance maximization model with twofold random phenomenon and its application to hydropower station operation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 85(C), pages 11-33.

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