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Adaptive Genetic Algorithm for Daily Optimal Operation of Cascade Reservoirs and its Improvement Strategy

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  • Kan Yang
  • Jiao Zheng
  • Min Yang
  • Ran Zhou
  • Guoshuai Liu

Abstract

For the specialty of cascade reservoirs optimization and the premature convergence of GA, several improvement strategies are presented in this paper. Firstly, solution space generation method is found application to generate feasible initial population. Secondly, chaos optimization is adopted to optimize initial population. Thirdly, new selective operators, trigonometric selective operators, are proposed to overcome the fitness requirement of non-negative and to maintain the diversity of population. Fourthly, adaptive probabilities of crossing and mutation are adopted in order to improve the convergence speed of GA. Besides, elitist strategy is used to ensure that the best individual can be remained in each generation. Furthermore, the performance of these proposed improvement strategies was checked against the historical improvement strategies by simulating optimal operation of Three Gorges cascade reservoirs premised on historical hourly inflows, and the comparison yields indications of superior performance. In these proposed improvement strategies, trigonometric selective operators are feasible and effective for optimizing operation of cascade reservoirs. These new selective operators could help GA to find a more excellent solution in the same algebra, and the performance of convergence speed is advanced. Adaptive probabilities of crossing and mutation have better performance than other improvement strategies, such as annealing chaotic mutation and simulated annealing of large probability of mutation, because this method realizes the twin goals of maintaining diversity in the population and advancing the convergence speed of GA. Copyright Springer Science+Business Media Dordrecht 2013

Suggested Citation

  • Kan Yang & Jiao Zheng & Min Yang & Ran Zhou & Guoshuai Liu, 2013. "Adaptive Genetic Algorithm for Daily Optimal Operation of Cascade Reservoirs and its Improvement Strategy," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(12), pages 4209-4235, September.
    • Handle: RePEc:spr:waterr:v:27:y:2013:i:12:p:4209-4235
    DOI: 10.1007/s11269-013-0403-3
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    References listed on IDEAS

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    1. Chun-Tian Cheng & Wen-Chuan Wang & Dong-Mei Xu & K. Chau, 2008. "Optimizing Hydropower Reservoir Operation Using Hybrid Genetic Algorithm and Chaos," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 22(7), pages 895-909, July.
    2. Fi-John Chang & Li Chen, 1998. "Real-Coded Genetic Algorithm for Rule-Based Flood Control Reservoir Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 12(3), pages 185-198, June.
    3. 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.
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    Cited by:

    1. Po-Kuan Chiang & Patrick Willems, 2015. "Combine Evolutionary Optimization with Model Predictive Control in Real-time Flood Control of a River System," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(8), pages 2527-2542, June.
    2. Hu Hu & Kan Yang & Lang Liu & Lyuwen Su & Zhe Yang, 2019. "Short-Term Hydropower Generation Scheduling Using an Improved Cloud Adaptive Quantum-Inspired Binary Social Spider Optimization Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(7), pages 2357-2379, May.
    3. T. Fowe & I. Nouiri & B. Ibrahim & H. Karambiri & J. Paturel, 2015. "OPTIWAM: An Intelligent Tool for Optimizing Irrigation Water Management in Coupled Reservoir–Groundwater Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(10), pages 3841-3861, August.

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