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Extracting Optimal Policies of Hydropower Multi-Reservoir Systems Utilizing Enhanced Differential Evolution Algorithm

Author

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  • Iman Ahmadianfar

    (Behbahan Khatam Alanbia University of Technology)

  • Arvin Samadi-Koucheksaraee

    (Behbahan Khatam Alanbia University of Technology)

  • Omid Bozorg-Haddad

    (University of Tehran)

Abstract

Deriving the optimal policies of hydropower multi-reservoir systems is a nonlinear and high-dimensional problem which makes it difficult to achieve the global or near global optimal solution. In order to optimally solve the problem effectively, development of optimization methods with the purpose of optimizing reservoir operation is indispensable as well as inevitable. This paper introduces an enhanced differential evolution (EDE) algorithm to enhance the exploration and exploitation abilities of the original differential evolution (DE) algorithm. The EDE algorithm is first applied to minimize two benchmark functions (Ackley and Shifted Schwefel). In addition, a real world two-reservoir hydropower optimization problem and a large scale benchmark problem, namely ten-reservoir problem, were considered to indicate the effectiveness of the EDE. The performance of the EDE was compared with the original DE to solve the three optimization problems. The results demonstrate that the EDE would have a powerful global ability and faster convergence than the original DE to solve the two benchmark functions. In the 10-reservoir optimization problem, the EDE proved to be much more functional to reach optimal or near optimal solution and to be effective in terms of convergence rate, standard deviation, the best, average and worst values of objective function than the original DE. Also, In the case of two-reservoir system, the best values of the objective function obtained 93.86 and 101.09 for EDE and DE respectively. Based on the results, it can be stated that the most important reason to improve the performance of the EDE algorithm is the promotion of local and global search abilities of the DE algorithm using the number of novel operators. Also, the results of these three problems corroborated the superior performance, the high efficiency and robustness of the EDE to optimize complex and large scale multi-reservoir operation problems.

Suggested Citation

  • Iman Ahmadianfar & Arvin Samadi-Koucheksaraee & Omid Bozorg-Haddad, 2017. "Extracting Optimal Policies of Hydropower Multi-Reservoir Systems Utilizing Enhanced Differential Evolution Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(14), pages 4375-4397, November.
    • Handle: RePEc:spr:waterr:v:31:y:2017:i:14:d:10.1007_s11269-017-1753-z
    DOI: 10.1007/s11269-017-1753-z
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    References listed on IDEAS

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    1. D. Kumar & M. Reddy, 2006. "Ant Colony Optimization for Multi-Purpose Reservoir Operation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 20(6), pages 879-898, December.
    2. Omid Haddad & Abbas Afshar & Miguel Mariño, 2006. "Honey-Bees Mating Optimization (HBMO) Algorithm: A New Heuristic Approach for Water Resources Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 20(5), pages 661-680, October.
    3. A. Vasan & Komaragiri Raju, 2007. "Application of Differential Evolution for Irrigation Planning: An Indian Case Study," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(8), pages 1393-1407, August.
    4. M. Afshar & R. Moeini, 2008. "Partially and Fully Constrained Ant Algorithms for the Optimal Solution of Large Scale Reservoir Operation Problems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 22(12), pages 1835-1857, December.
    5. Mohamed Louati & Sihem Benabdallah & Fethi Lebdi & Darko Milutin, 2011. "Application of a Genetic Algorithm for the Optimization of a Complex Reservoir System in Tunisia," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(10), pages 2387-2404, August.
    6. Juran Ahmed & Arup Sarma, 2005. "Genetic Algorithm for Optimal Operating Policy of a Multipurpose Reservoir," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 19(2), pages 145-161, April.
    7. M. Jalali & A. Afshar & M. Mariño, 2007. "Multi-Colony Ant Algorithm for Continuous Multi-Reservoir Operation Optimization Problem," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(9), pages 1429-1447, September.
    8. Omid Bozorg Haddad & Abbas Afshar & Miguel Mariño, 2008. "Design-Operation of Multi-Hydropower Reservoirs: HBMO Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 22(12), pages 1709-1722, December.
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    1. Qiao-feng Tan & Guo-hua Fang & Xin Wen & Xiao-hui Lei & Xu Wang & Chao Wang & Yi Ji, 2020. "Bayesian Stochastic Dynamic Programming for Hydropower Generation Operation Based on Copula Functions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(5), pages 1589-1607, March.
    2. Ahmadianfar, Iman & Kheyrandish, Ali & Jamei, Mehdi & Gharabaghi, Bahram, 2021. "Optimizing operating rules for multi-reservoir hydropower generation systems: An adaptive hybrid differential evolution algorithm," Renewable Energy, Elsevier, vol. 167(C), pages 774-790.
    3. Vartika Paliwal & Aniruddha D. Ghare & Ashwini B. Mirajkar & Neeraj Dhanraj Bokde & Andrés Elías Feijóo Lorenzo, 2019. "Computer Modeling for the Operation Optimization of Mula Reservoir, Upper Godavari Basin, India, Using the Jaya Algorithm," Sustainability, MDPI, vol. 12(1), pages 1-21, December.
    4. 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.
    5. Ahmadianfar, Iman & Samadi-Koucheksaraee, Arvin & Razavi, Saman, 2023. "Design of optimal operating rule curves for hydropower multi-reservoir systems by an influential optimization method," Renewable Energy, Elsevier, vol. 211(C), pages 508-521.
    6. Mehrdad Taghian & Iman Ahmadianfar, 2018. "Maximizing the Firm Energy Yield Preserving Total Energy Generation Via an Optimal Reservoir Operation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(1), pages 141-154, January.
    7. Iman Ahmadianfar & Reza Zamani, 2020. "Assessment of the hedging policy on reservoir operation for future drought conditions under climate change," Climatic Change, Springer, vol. 159(2), pages 253-268, March.
    8. Kobra Rahmati & Parisa-Sadat Ashofteh & Hugo A. Loáiciga, 2021. "Application of the Grasshopper Optimization Algorithm (GOA) to the Optimal Operation of Hydropower Reservoir Systems Under Climate Change," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(13), pages 4325-4348, October.
    9. Iman Ahmadianfar & Saeed Noshadian & Nadir Ahmed Elagib & Meysam Salarijazi, 2021. "Robust Diversity-based Sine-Cosine Algorithm for Optimizing Hydropower Multi-reservoir Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(11), pages 3513-3538, September.

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