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Water Resources Management

, Volume 27, Issue 7, pp 1963–1979 | Cite as

Optimization of Hydropower Reservoir Using Evolutionary Algorithms Coupled with Chaos

Article

Abstract

Over the past decade, several conventional optimization techniques had been developed for the optimization of complex water resources system. To overcome some of the drawbacks of conventional techniques, soft computing techniques were developed based on the principles of natural evolution. The major difference between the conventional optimization techniques and soft computing is that in the former case, the optimal solution is derived where as in the soft computing techniques, it is searched from a randomly generated population of possible solutions. The results of the evolutionary algorithm mainly depend on the randomly generated initial population that is arrived based on the probabilistic theory. Recent research findings proved that most of the water resources variables exhibit chaotic behavior, which is a projection depends upon the initial condition. In the present study, the chaos algorithm is coupled with evolutionary optimization algorithms such as genetic algorithm (GA) and differential evolution (DE) algorithm for generating the initial population and applied for maximizing the hydropower production from a reservoir. The results are then compared with conventional genetic algorithm and differential evolution algorithm. The results show that the chaotic differential evolution (CDE) algorithm performs better than other techniques in terms of total annual power production. This study also shows that the chaos algorithm has enriched the search of general optimization algorithm and thus may be used for optimizing complex non-linear water resources systems.

Keywords

Chaos algorithm Differential evolution algorithm Genetic algorithm Optimization Hydropower system 

Notes

Acknowledgement

The financial support of Ministry of Water Resources, Government of India, New Delhi, through the Indian National Committee on Hydrology for this research work is gratefully acknowledged. The authors also thank Chief Engineer, Koyna Hydroelectric Project and Executive Engineer, Koyna Dam for providing necessary data.

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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.Department of Civil EngineeringIndian Institute of Technology BombayMumbaiIndia

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