Multiple Hydropower Reservoirs Operation by Hyperbolic Grey Wolf Optimizer Based on Elitism Selection and Adaptive Mutation

Multiple hydropower reservoirs operation is an effective measure to rationally allocate the limited water resources under uncertainty. With the rapid expansion of water resources system, it becomes much more difficult for traditional methods to quickly yield the reasonable operational policy. Grey w...

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Bibliographic Details
Published in:Water resources management 2021, Vol.35 (2), p.573-591
Main Authors: Niu, Wen-jing, Feng, Zhong-kai, Liu, Shuai, Chen, Yu-bin, Xu, Yin-shan, Zhang, Jun
Format: Article
Language:English
Subjects:
Atmospheric Sciences
Civil Engineering
Control methods
Convergence
Defects
Earth and Environmental Science
Earth Sciences
Elitism
Environment
Geotechnical Engineering & Applied Earth Sciences
Heuristic methods
Hunting
Hydroelectric power
Hydrogeology
Hydrology/Water Resources
Mutation
Optimization
Reservoirs
Searching
Strategy
Water resources
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Summary:Multiple hydropower reservoirs operation is an effective measure to rationally allocate the limited water resources under uncertainty. With the rapid expansion of water resources system, it becomes much more difficult for traditional methods to quickly yield the reasonable operational policy. Grey wolf optimizer, inspired by the wolves’ hunting behaviors, is a famous metaheuristic method to resolve engineering optimization problems, but still suffers from the local convergence and search stagnation defects. To alleviate this problem, this study proposes a hybrid grey wolf optimizer (HGWO) where the hyperbolic accelerating strategy is introduced to improve the local search ability; the adaptive mutation strategy is used to diversify the swarm; the elitism selection strategy is used to enhance the convergence speed. The experimental results show that the HGWO method can produce better solutions than its original version in several test functions. Then, the HGWO method is applied to resolve the optimal operation of a real-world hydropower system with the goal of maximizing the total generation benefit. The simulations indicate that the HGWO method produces satisfying scheduling schemes than several control methods in terms of all the statistical indicators. Hence, with the merits of superior search ability, rapid convergence rate and gradient information avoidance, HGWO proves to be a promising alternative optimization tool for the complex multireservoir system operation problem.
ISSN:0920-4741
1573-1650
DOI:10.1007/s11269-020-02737-8