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Deriving Hedging Rules of Multi-Reservoir System by Online Evolving Neural Networks

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  • Alireza Dariane
  • Farzane Karami

Abstract

This paper presents an online optimization scheme for combined use of Artificial Neural Networks (ANN), hedging policies and harmony search algorithm (HS) in developing optimum operating policies for Tehran water resources system. Past efforts in this area are concentrated on using an offline approach. In that approach, an optimization method is first used to derive a long-term set of optimum reservoir releases. These releases are then used as the target vector for training the ANN model. The online method simultaneously uses the optimization and ANN methods and can adopt objective functions other than minimizing the error indices. Therefore, it requires methods other than the backpropagation for training the ANN model. Hence, under the proposed online approach the application of a heuristic method, such as HS, is inevitable for training the network. This is accomplished by using an optimization-simulation procedure where different objective functions and system constraints could be easily handled. The proposed approach is a novel and efficient method for finding the parameters of hedging policies where earlier methods suffered from high computational costs and the curse of dimensionality. The results show the superiority of the proposed online scheme. Moreover, a surrogate model for the hedging policy is presented, which by adhering to the principle of parsimony is more efficient in large scale systems involving many decision variables. Copyright Springer Science+Business Media Dordrecht 2014

Suggested Citation

  • 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.
    • Handle: RePEc:spr:waterr:v:28:y:2014:i:11:p:3651-3665
    DOI: 10.1007/s11269-014-0693-0
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    References listed on IDEAS

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    1. A. Cancelliere & G. Giuliano & A. Ancarani & G. Rossi, 2002. "A Neural Networks Approach for Deriving Irrigation Reservoir Operating Rules," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 16(1), pages 71-88, February.
    2. T. Neelakantan & N. Pundarikanthan, 1999. "Hedging Rule Optimisation for Water Supply Reservoirs System," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 13(6), pages 409-426, December.
    3. Shih, Jhih-Shyang & ReVelle, Charles, 1995. "Water supply operations during drought: A discrete hedging rule," European Journal of Operational Research, Elsevier, vol. 82(1), pages 163-175, April.
    4. J. Shiau & H. Lee, 2005. "Derivation of Optimal Hedging Rules for a Water-supply Reservoir through Compromise Programming," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 19(2), pages 111-132, April.
    5. 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.
    6. K. Srinivasan & M. Philipose, 1998. "Effect of Hedging on Over-Year Reservoir Performance," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 12(2), pages 95-120, April.
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    Cited by:

    1. Jenq-Tzong Shiau & Hui-Ting Hsu, 2016. "Suitability of ANN-Based Daily Streamflow Extension Models: a Case Study of Gaoping River Basin, Taiwan," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(4), pages 1499-1513, March.
    2. Jenq-Tzong Shiau & Hui-Ting Hsu, 2016. "Suitability of ANN-Based Daily Streamflow Extension Models: a Case Study of Gaoping River Basin, Taiwan," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(4), pages 1499-1513, March.
    3. Zhenfang He & Yaonan Zhang & Qingchun Guo & Xueru Zhao, 2014. "Comparative Study of Artificial Neural Networks and Wavelet Artificial Neural Networks for Groundwater Depth Data Forecasting with Various Curve Fractal Dimensions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(15), pages 5297-5317, December.
    4. A. B. Dariane & M. Farhani & Sh Azimi, 2018. "Long Term Streamflow Forecasting Using a Hybrid Entropy Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(4), pages 1439-1451, March.
    5. A. B. Dariane & E. Pouryafar, 2021. "Quantifying and projection of the relative impacts of climate change and direct human activities on streamflow fluctuations," Climatic Change, Springer, vol. 165(1), pages 1-20, March.
    6. Behrang Beiranvand & Parisa-Sadat Ashofteh, 2023. "A Systematic Review of Optimization of Dams Reservoir Operation Using the Meta-heuristic Algorithms," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(9), pages 3457-3526, July.
    7. A. J. Adeloye & B.-S. Soundharajan & C. S. P. Ojha & R. Remesan, 2016. "Effect of Hedging-Integrated Rule Curves on the Performance of the Pong Reservoir (India) During Scenario-Neutral Climate Change Perturbations," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(2), pages 445-470, January.
    8. Javad Jamshidi & Mojtaba Shourian, 2019. "Hedging Rules-Based Optimal Reservoir Operation Using Bat Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(13), pages 4525-4538, October.
    9. A. Adeloye & B.-S. Soundharajan & C. Ojha & R. Remesan, 2016. "Effect of Hedging-Integrated Rule Curves on the Performance of the Pong Reservoir (India) During Scenario-Neutral Climate Change Perturbations," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(2), pages 445-470, January.

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